hfModelId large_stringlengths 11 68 | smModelId large_stringlengths 15 86 ⌀ | serverlessCustomizationSupport bool 2
classes | serverfulTrainingSupport bool 2
classes | deployAvailability bool 1
class | trainingAvailability bool 2
classes | hasMultipleVariants bool 2
classes | endpointCode large_stringlengths 380 1.25k ⌀ | endpointLinks large_stringclasses 10
values | training_hfCode large_stringclasses 36
values | training_hfLinks large_stringclasses 3
values | deployRedirectionLink large_stringlengths 153 272 ⌀ | customizeRedirectionLink large_stringlengths 206 266 ⌀ | dpoCode large_stringclasses 26
values | dpoLabel large_stringclasses 1
value | dpoLinks large_stringclasses 1
value | rlaifCode large_stringclasses 29
values | rlaifLabel large_stringclasses 1
value | rlaifLinks large_stringclasses 1
value | rlvrCode large_stringclasses 29
values | rlvrLabel large_stringclasses 1
value | rlvrLinks large_stringclasses 1
value | sftCode large_stringclasses 29
values | sftLabel large_stringclasses 1
value | sftLinks large_stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
01-ai/Yi-1.5-34B | huggingface-llm-yi-1-5-34b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-yi-1-5-34b")
example_payloads = model.retrieve_... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=01-ai%2Fyi-1.5-34b&smModelId=huggingface-llm-yi-1-5-34b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
01-ai/Yi-1.5-9B | huggingface-llm-yi-1-5-9b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-yi-1-5-9b")
example_payloads = model.retrieve_a... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=01-ai%2Fyi-1.5-9b&smModelId=huggingface-llm-yi-1-5-9b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Alibaba-NLP/gte-Qwen2-7B-instruct | huggingface-textembedding-gte-qwen2-7b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-textembedding-gte-qwen2-7b-instruct")
example_paylo... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=alibaba-nlp%2Fgte-qwen2-7b-instruct&smModelId=huggingface-textembedding-gte-qwen2-7b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
BAAI/bge-base-en | huggingface-sentencesimilarity-bge-base-en | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-bge-base-en"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input)
prin... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-base-en&smModelId=huggingface-sentencesimilarity-bge-base-en&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-base-en&smModelId=huggingface-sentencesimilarity-bge-base-en&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
BAAI/bge-base-en-v1.5 | huggingface-sentencesimilarity-bge-base-en-v1-5 | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-bge-base-en-v1-5"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input)... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-base-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-base-en-v1-5&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-base-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-base-en-v1-5&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
BAAI/bge-large-en | huggingface-sentencesimilarity-bge-large-en | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-bge-large-en"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input)
pri... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-large-en&smModelId=huggingface-sentencesimilarity-bge-large-en&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-large-en&smModelId=huggingface-sentencesimilarity-bge-large-en&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
BAAI/bge-large-en-v1.5 | huggingface-sentencesimilarity-bge-large-en-v1-5 | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-bge-large-en-v1-5"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-large-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-large-en-v1-5&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-large-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-large-en-v1-5&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
BAAI/bge-m3 | huggingface-sentencesimilarity-bge-m3 | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-bge-m3"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input)
print(f"I... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-m3&smModelId=huggingface-sentencesimilarity-bge-m3&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-m3&smModelId=huggingface-sentencesimilarity-bge-m3&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
BAAI/bge-small-en | huggingface-sentencesimilarity-bge-small-en | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-bge-small-en"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input)
pri... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-small-en&smModelId=huggingface-sentencesimilarity-bge-small-en&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-small-en&smModelId=huggingface-sentencesimilarity-bge-small-en&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
BAAI/bge-small-en-v1.5 | huggingface-sentencesimilarity-bge-small-en-v1-5 | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-bge-small-en-v1-5"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-small-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-small-en-v1-5&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-small-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-small-en-v1-5&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
Bingsu/my-korean-stable-diffusion-v1-5 | huggingface-txt2img-bingsu-my-korean-stable-diffusion-v1-5 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-txt2img-bingsu-my-korean-stable-diffusion-v1-5")
ex... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=bingsu%2Fmy-korean-stable-diffusion-v1-5&smModelId=huggingface-txt2img-bingsu-my-korean-stable-diffusion-v1-5&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
CohereLabs/aya-101 | huggingface-llm-aya-101 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-aya-101")
example_payloads = model.retrieve_all... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=coherelabs%2Faya-101&smModelId=huggingface-llm-aya-101&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
EleutherAI/gpt-j-6b | huggingface-textgeneration1-gpt-j-6b | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-textgeneration1-gpt-j-6b")
example_payloads = model... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fgpt-j-6b&smModelId=huggingface-textgeneration1-gpt-j-6b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fgpt-j-6b&smModelId=huggingface-textgeneration1-gpt-j-6b&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
EleutherAI/gpt-neo-125m | huggingface-textgeneration1-gpt-neo-125m | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-textgeneration1-gpt-neo-125m")
example_payloads = m... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fgpt-neo-125m&smModelId=huggingface-textgeneration1-gpt-neo-125m&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fgpt-neo-125m&smModelId=huggingface-textgeneration1-gpt-neo-125m&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
EleutherAI/pythia-160m-deduped | huggingface-llm-eleutherai-pythia-160m-deduped | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-eleutherai-pythia-160m-deduped")
example_payloa... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fpythia-160m-deduped&smModelId=huggingface-llm-eleutherai-pythia-160m-deduped&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
EleutherAI/pythia-70m-deduped | huggingface-llm-eleutherai-pythia-70m-deduped | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-eleutherai-pythia-70m-deduped")
example_payload... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fpythia-70m-deduped&smModelId=huggingface-llm-eleutherai-pythia-70m-deduped&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
FacebookAI/roberta-base | huggingface-eqa-roberta-base | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-roberta-base")
example_payloads = model.retriev... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=facebookai%2Froberta-base&smModelId=huggingface-eqa-roberta-base&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=facebookai%2Froberta-base&smModelId=huggingface-eqa-roberta-base&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
FacebookAI/roberta-large | huggingface-eqa-roberta-large | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-roberta-large")
example_payloads = model.retrie... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=facebookai%2Froberta-large&smModelId=huggingface-eqa-roberta-large&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=facebookai%2Froberta-large&smModelId=huggingface-eqa-roberta-large&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null | null | null | null |
Fictiverse/Stable_Diffusion_BalloonArt_Model | huggingface-txt2img-fictiverse-stable-diffusion-balloonart-model | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-txt2img-fictiverse-stable-diffusion-balloonart")
ex... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=fictiverse%2Fstable_diffusion_balloonart_model&smModelId=huggingface-txt2img-fictiverse-stable-diffusion-balloonart-model&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Fictiverse/Stable_Diffusion_Microscopic_model | huggingface-txt2img-fictiverse-stable-diffusion-microscopic-model | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-txt2img-fictiverse-stable-diffusion-micro-model")
e... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=fictiverse%2Fstable_diffusion_microscopic_model&smModelId=huggingface-txt2img-fictiverse-stable-diffusion-microscopic-model&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Fictiverse/Stable_Diffusion_PaperCut_Model | huggingface-txt2img-fictiverse-stable-diffusion-papercut-model | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-txt2img-fictiverse-stable-diffusion-papercut-model"... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=fictiverse%2Fstable_diffusion_papercut_model&smModelId=huggingface-txt2img-fictiverse-stable-diffusion-papercut-model&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Fictiverse/Stable_Diffusion_VoxelArt_Model | huggingface-txt2img-fictiverse-stable-diffusion-voxelart-model | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-txt2img-fictiverse-stable-diffusion-voxelart-model"... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=fictiverse%2Fstable_diffusion_voxelart_model&smModelId=huggingface-txt2img-fictiverse-stable-diffusion-voxelart-model&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Helsinki-NLP/opus-mt-en-es | huggingface-translation-opus-mt-en-es | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-translation-opus-mt-en-es"
endpoint_input = "My name is Wolfgang and I l... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=helsinki-nlp%2Fopus-mt-en-es&smModelId=huggingface-translation-opus-mt-en-es&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Helsinki-NLP/opus-mt-en-vi | huggingface-translation-opus-mt-en-vi | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-translation-opus-mt-en-vi"
endpoint_input = "My name is Wolfgang and I l... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=helsinki-nlp%2Fopus-mt-en-vi&smModelId=huggingface-translation-opus-mt-en-vi&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Helsinki-NLP/opus-mt-mul-en | huggingface-translation-opus-mt-mul-en | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-translation-opus-mt-mul-en"
endpoint_input = "My name is Wolfgang and I ... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=helsinki-nlp%2Fopus-mt-mul-en&smModelId=huggingface-translation-opus-mt-mul-en&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
HuggingFaceH4/starchat-alpha | huggingface-llm-huggingfaceh4-starchat-alpha | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-huggingfaceh4-starchat-alpha")
example_payloads... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=huggingfaceh4%2Fstarchat-alpha&smModelId=huggingface-llm-huggingfaceh4-starchat-alpha&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
HuggingFaceH4/starchat-beta | huggingface-llm-huggingfaceh4-starchat-beta | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-huggingfaceh4-starchat-beta")
example_payloads ... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=huggingfaceh4%2Fstarchat-beta&smModelId=huggingface-llm-huggingfaceh4-starchat-beta&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
HuggingFaceH4/zephyr-7b-beta | huggingface-llm-huggingfaceh4-zephyr-7b-beta | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-huggingfaceh4-zephyr-7b-beta")
example_payloads... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=huggingfaceh4%2Fzephyr-7b-beta&smModelId=huggingface-llm-huggingfaceh4-zephyr-7b-beta&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1 | huggingface-llm-huggingfaceh4-zephyr-orpo-141b-a35b-v01 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-huggingfaceh4-zephyr-orpo-141b-a35b-v01")
examp... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=huggingfaceh4%2Fzephyr-orpo-141b-a35b-v0.1&smModelId=huggingface-llm-huggingfaceh4-zephyr-orpo-141b-a35b-v01&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-EN-v0.1 | huggingface-txt2img-idea-ccnl-taiyi-stable-diffusion-1b-chinese-en-v0-1 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-txt2img-idea-ccnl-taiyi-1b-chinese-en-v01")
example... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=idea-ccnl%2Ftaiyi-stable-diffusion-1b-chinese-en-v0.1&smModelId=huggingface-txt2img-idea-ccnl-taiyi-stable-diffusion-1b-chinese-en-v0-1&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1 | huggingface-txt2img-idea-ccnl-taiyi-stable-diffusion-1b-chinese-v0-1 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-txt2img-idea-ccnl-taiyi-1b-chinese-v0-1")
example_p... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=idea-ccnl%2Ftaiyi-stable-diffusion-1b-chinese-v0.1&smModelId=huggingface-txt2img-idea-ccnl-taiyi-stable-diffusion-1b-chinese-v0-1&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Langboat/Guohua-Diffusion | huggingface-txt2img-langboat-guohua-diffusion | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-txt2img-langboat-guohua-diffusion")
example_payload... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=langboat%2Fguohua-diffusion&smModelId=huggingface-txt2img-langboat-guohua-diffusion&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
MiniMaxAI/MiniMax-M2 | huggingface-llm-minimax-m2 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-minimax-m2")
example_payloads = model.retrieve_... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=minimaxai%2Fminimax-m2&smModelId=huggingface-llm-minimax-m2&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
MiniMaxAI/MiniMax-M2.1 | huggingface-llm-minimax-m2-1 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-minimax-m2-1")
example_payloads = model.retriev... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=minimaxai%2Fminimax-m2.1&smModelId=huggingface-llm-minimax-m2-1&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
MiniMaxAI/MiniMax-M2.5 | huggingface-llm-minimax-m2-5 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-minimax-m2-5")
example_payloads = model.retriev... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=minimaxai%2Fminimax-m2.5&smModelId=huggingface-llm-minimax-m2-5&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
MiniMaxAI/MiniMax-M2.7 | huggingface-llm-minimax-m2-7 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-minimax-m2-7")
example_payloads = model.retriev... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=minimaxai%2Fminimax-m2.7&smModelId=huggingface-llm-minimax-m2-7&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 | huggingface-zstc-moritzlaurer-mdeberta-v3-base-xnli-multilingual-nli-2mil7 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-moritzlaurer-mdeberta3base-xnli-mling-nli-2m7"
endpoint_input = {'s... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=moritzlaurer%2Fmdeberta-v3-base-xnli-multilingual-nli-2mil7&smModelId=huggingface-zstc-moritzlaurer-mdeberta-v3-base-xnli-multilingual-nli-2mil7&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Narsil/deberta-large-mnli-zero-cls | huggingface-zstc-narsil-deberta-large-mnli-zero-cls | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-narsil-deberta-large-mnli-zero-cls"
endpoint_input = {'sequences': ... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=narsil%2Fdeberta-large-mnli-zero-cls&smModelId=huggingface-zstc-narsil-deberta-large-mnli-zero-cls&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
NexaAI/Octopus-v2 | huggingface-llm-nexaaidev-octopus-v2 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-nexaaidev-octopus-v2")
example_payloads = model... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=nexaai%2Foctopus-v2&smModelId=huggingface-llm-nexaaidev-octopus-v2&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Nexusflow/Starling-LM-7B-beta | huggingface-llm-nexusflow-starling-lm-7b-beta | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-nexusflow-starling-lm-7b-beta")
example_payload... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=nexusflow%2Fstarling-lm-7b-beta&smModelId=huggingface-llm-nexusflow-starling-lm-7b-beta&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
NousResearch/Hermes-2-Pro-Llama-3-8B | huggingface-llm-nousresearch-hermes-2-pro-llama-3-8B | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-nousresearch-hermes-2-pro-llama-3-8B")
example_... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=nousresearch%2Fhermes-2-pro-llama-3-8b&smModelId=huggingface-llm-nousresearch-hermes-2-pro-llama-3-8B&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
NousResearch/Nous-Hermes-2-SOLAR-10.7B | huggingface-llm-nousresearch-nous-hermes-2-solar-10-7b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-nousresearch-nous-hermes-2-solar-10-7b")
exampl... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=nousresearch%2Fnous-hermes-2-solar-10.7b&smModelId=huggingface-llm-nousresearch-nous-hermes-2-solar-10-7b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/QVQ-72B-Preview | huggingface-vlm-qvq-72b-preview | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qvq-72b-preview"
model = JumpStartModel(model_id=model_id)
payload ... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqvq-72b-preview&smModelId=huggingface-vlm-qvq-72b-preview&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/QwQ-32B | huggingface-llm-qwq-32b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwq-32b")
example_payloads = model.retrieve_all... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwq-32b&smModelId=huggingface-llm-qwq-32b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen2-0.5B | huggingface-llm-qwen2-0-5b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-0-5b")
example_payloads = model.retrieve_... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-0.5b&smModelId=huggingface-llm-qwen2-0-5b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen2-0.5B-Instruct | huggingface-llm-qwen2-0-5b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-0-5b-instruct")
example_payloads = model.... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-0.5b-instruct&smModelId=huggingface-llm-qwen2-0-5b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen2-1.5B-Instruct | huggingface-llm-qwen2-1-5b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-1-5b-instruct")
example_payloads = model.... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-1.5b-instruct&smModelId=huggingface-llm-qwen2-1-5b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen2-7B | huggingface-llm-qwen2-7b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-7b")
example_payloads = model.retrieve_al... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-7b&smModelId=huggingface-llm-qwen2-7b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen2-7B-Instruct | huggingface-llm-qwen2-7b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-7b-instruct")
example_payloads = model.re... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-7b-instruct&smModelId=huggingface-llm-qwen2-7b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen2-VL-7B-Instruct | huggingface-vlm-qwen2-vl-7b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qwen2-vl-7b-instruct"
model = JumpStartModel(model_id=model_id)
pay... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-vl-7b-instruct&smModelId=huggingface-vlm-qwen2-vl-7b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen2.5-14B-Instruct | huggingface-llm-qwen2-5-14b-instruct | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-5-14b-instruct")
example_payloads = model... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-14b-instruct&smModelId=huggingface-llm-qwen2-5-14b-instruct&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-14b-instruct&smModelId=huggingface-llm-qwen2-5-14b-instruct&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen2.5-32B-Instruct | huggingface-llm-qwen2-5-32b-instruct | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-5-32b-instruct")
example_payloads = model... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-32b-instruct&smModelId=huggingface-llm-qwen2-5-32b-instruct&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-32b-instruct&smModelId=huggingface-llm-qwen2-5-32b-instruct&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen2.5-72B-Instruct | huggingface-llm-qwen2-5-72b-instruct | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-5-72b-instruct")
example_payloads = model... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-72b-instruct&smModelId=huggingface-llm-qwen2-5-72b-instruct&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-72b-instruct&smModelId=huggingface-llm-qwen2-5-72b-instruct&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen2.5-7B-Instruct | huggingface-llm-qwen2-5-7b-instruct | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-5-7b-instruct")
example_payloads = model.... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-7b-instruct&smModelId=huggingface-llm-qwen2-5-7b-instruct&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-7b-instruct&smModelId=huggingface-llm-qwen2-5-7b-instruct&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen2.5-Coder-32B-Instruct | huggingface-llm-qwen2-5-coder-32b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-5-coder-32b-instruct")
example_payloads =... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-coder-32b-instruct&smModelId=huggingface-llm-qwen2-5-coder-32b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen2.5-Coder-7B-Instruct | huggingface-llm-qwen2-5-coder-7b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-qwen2-5-coder-7b-instruct")
example_payloads = ... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-coder-7b-instruct&smModelId=huggingface-llm-qwen2-5-coder-7b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-0.6B | huggingface-reasoning-qwen3-06b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-06b")
example_payloads = model.retr... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-0.6b&smModelId=huggingface-reasoning-qwen3-06b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-0.6b&smModelId=huggingface-reasoning-qwen3-06b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3-1.7B | huggingface-reasoning-qwen3-1-7b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-1-7b")
example_payloads = model.ret... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-1.7b&smModelId=huggingface-reasoning-qwen3-1-7b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-1.7b&smModelId=huggingface-reasoning-qwen3-1-7b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3-14B | huggingface-reasoning-qwen3-14b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-14b")
example_payloads = model.retr... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-14b&smModelId=huggingface-reasoning-qwen3-14b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-14b&smModelId=huggingface-reasoning-qwen3-14b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3-30B-A3B | huggingface-reasoning-qwen3-30b-a3b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-30b-a3b")
example_payloads = model.... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-30b-a3b&smModelId=huggingface-reasoning-qwen3-30b-a3b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-30B-A3B-Instruct-2507 | huggingface-reasoning-qwen3-30b-a3b-instruct-2507 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-30b-a3b-instruct-2507")
example_pay... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-falcon.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-30b-a3b-instruct-2507&smModelId=huggingface-reasoning-qwen3-30b-a3b-instruct-2507&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-30B-A3B-Thinking-2507 | huggingface-reasoning-qwen3-30b-a3b-thinking-2507 | false | false | true | false | false | # Deploy a JumpStart model using the SageMaker Python SDK v3.
from sagemaker.serve.model_builder import ModelBuilder
from sagemaker.core.jumpstart.configs import JumpStartConfig
from sagemaker.core.training.configs import Compute
model_builder = ModelBuilder.from_jumpstart_config(
jumpstart_config=JumpStartConfig... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-30b-a3b-thinking-2507&smModelId=huggingface-reasoning-qwen3-30b-a3b-thinking-2507&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-32B | huggingface-reasoning-qwen3-32b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-32b")
example_payloads = model.retr... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-32b&smModelId=huggingface-reasoning-qwen3-32b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-32b&smModelId=huggingface-reasoning-qwen3-32b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3-4B | huggingface-reasoning-qwen3-4b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-4b")
example_payloads = model.retri... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-4b&smModelId=huggingface-reasoning-qwen3-4b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-4b&smModelId=huggingface-reasoning-qwen3-4b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3-4B-Instruct-2507 | huggingface-reasoning-qwen3-4b-instruct-2507 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-4b-instruct-2507")
example_payloads... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-4b-instruct-2507&smModelId=huggingface-reasoning-qwen3-4b-instruct-2507&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-8B | huggingface-reasoning-qwen3-8b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-8b")
example_payloads = model.retri... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-8b&smModelId=huggingface-reasoning-qwen3-8b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-8b&smModelId=huggingface-reasoning-qwen3-8b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3-ASR-1.7B | huggingface-asr-qwen3-asr-1-7b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-asr-qwen3-asr-1-7b")
example_payloads = model.retri... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-asr-1.7b&smModelId=huggingface-asr-qwen3-asr-1-7b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-Coder-30B-A3B-Instruct | huggingface-reasoning-qwen3-coder-30b-a3b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-coder-30b-a3b-instruct")
example_pa... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-coder-30b-a3b-instruct&smModelId=huggingface-reasoning-qwen3-coder-30b-a3b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-Coder-Next | huggingface-reasoning-qwen3-coder-next | false | false | true | false | false | # Deploy a JumpStart model using the SageMaker Python SDK v3.
from sagemaker.serve.model_builder import ModelBuilder
from sagemaker.core.jumpstart.configs import JumpStartConfig
from sagemaker.core.training.configs import Compute
model_builder = ModelBuilder.from_jumpstart_config(
jumpstart_config=JumpStartConfig... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-coder-next&smModelId=huggingface-reasoning-qwen3-coder-next&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-Embedding-0.6B | null | false | null | true | false | null | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-textembedding-qwen3-embedding-0-6b")
example_payloa... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-Next-80B-A3B-Instruct | huggingface-reasoning-qwen3-next-80b-a3b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-reasoning-qwen3-next-80b-a3b-instruct")
example_pay... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-falcon.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-next-80b-a3b-instruct&smModelId=huggingface-reasoning-qwen3-next-80b-a3b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-Reranker-4B | huggingface-textembedding-qwen3-reranker-4b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-textembedding-qwen3-reranker-4b")
example_payloads ... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-reranker-4b&smModelId=huggingface-textembedding-qwen3-reranker-4b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-TTS-12Hz-1.7B-Base | null | false | null | true | false | null | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-ttsvoiceclone-qwen3-tts-12hz-1-7b-base")
example_pa... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice | null | false | null | true | false | null | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-tts-qwen3-tts-customvoice")
example_payloads = mode... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-VL-8B-Instruct | huggingface-vlm-qwen3-vl-8b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qwen3-vl-8b-instruct"
model = JumpStartModel(model_id=model_id)
pay... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-vl-8b-instruct&smModelId=huggingface-vlm-qwen3-vl-8b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3-VL-Embedding-2B | huggingface-textembedding-qwen3-vl-embedding-2b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-textembedding-qwen3-vl-embedding-2b")
example_paylo... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-vl-embedding-2b&smModelId=huggingface-textembedding-qwen3-vl-embedding-2b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3.5-0.8B | huggingface-vlm-qwen3-5-0-8b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qwen3-5-0-8b"
model = JumpStartModel(model_id=model_id)
payload = m... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-0.8b&smModelId=huggingface-vlm-qwen3-5-0-8b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3.5-27B | huggingface-vlm-qwen3-5-27b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qwen3-5-27b"
model = JumpStartModel(model_id=model_id)
payload = mo... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-27b&smModelId=huggingface-vlm-qwen3-5-27b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-27b&smModelId=huggingface-vlm-qwen3-5-27b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3.5-27B-FP8 | huggingface-vlm-qwen3-5-27b-fp8 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qwen3-5-27b-fp8"
model = JumpStartModel(model_id=model_id)
payload ... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-27b-fp8&smModelId=huggingface-vlm-qwen3-5-27b-fp8&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3.5-2B | huggingface-vlm-qwen3-5-2b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qwen3-5-2b"
model = JumpStartModel(model_id=model_id)
payload = mod... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-2b&smModelId=huggingface-vlm-qwen3-5-2b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Qwen/Qwen3.5-4B | huggingface-vlm-qwen3-5-4b | true | false | true | true | false | # Deploy a JumpStart model using the SageMaker Python SDK v3.
from sagemaker.serve.model_builder import ModelBuilder
from sagemaker.core.jumpstart.configs import JumpStartConfig
from sagemaker.core.training.configs import Compute
model_builder = ModelBuilder.from_jumpstart_config(
jumpstart_config=JumpStartConfig... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-4b&smModelId=huggingface-vlm-qwen3-5-4b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-4b&smModelId=huggingface-vlm-qwen3-5-4b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | null | null | null | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3.5-9B | huggingface-vlm-qwen3-5-9b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qwen3-5-9b"
model = JumpStartModel(model_id=model_id)
payload = mod... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-9b&smModelId=huggingface-vlm-qwen3-5-9b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-9b&smModelId=huggingface-vlm-qwen3-5-9b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3.6-27B | huggingface-vlm-qwen3-6-27b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qwen3-6-27b"
model = JumpStartModel(model_id=model_id)
payload = mo... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.6-27b&smModelId=huggingface-vlm-qwen3-6-27b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.6-27b&smModelId=huggingface-vlm-qwen3-6-27b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | # Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3.
from sagemaker.train.dpo_trainer import DPOTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje... | Direct Preference Optimization (DPO) | [] | # Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3.
from sagemaker.train.rlaif_trainer import RLAIFTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "... | RL from AI Feedback (RLAIF) | [] | # Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3.
from sagemaker.train.rlvr_trainer import RLVRTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun... | RL with Verifiable Rewards (RLVR) | [] | # Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3.
from sagemaker.train.sft_trainer import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.ai_registry.dataset import DataSet
# Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line
# Download ... | Supervised Fine-Tuning (SFT) | [] |
Qwen/Qwen3.6-35B-A3B | huggingface-vlm-qwen3-6-35b-a3b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-qwen3-6-35b-a3b"
model = JumpStartModel(model_id=model_id)
payload ... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.6-35b-a3b&smModelId=huggingface-vlm-qwen3-6-35b-a3b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Recognai/bert-base-spanish-wwm-cased-xnli | huggingface-zstc-recognai-bert-base-spanish-wwm-cased-xnli | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-recognai-bert-base-spanish-wwm-cased-xnli"
endpoint_input = {'seque... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=recognai%2Fbert-base-spanish-wwm-cased-xnli&smModelId=huggingface-zstc-recognai-bert-base-spanish-wwm-cased-xnli&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
Recognai/zeroshot_selectra_medium | huggingface-zstc-recognai-zeroshot-selectra-medium | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-recognai-zeroshot-selectra-medium"
endpoint_input = {'sequences': '... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=recognai%2Fzeroshot_selectra_medium&smModelId=huggingface-zstc-recognai-zeroshot-selectra-medium&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null | null | null | null |
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