Instructions to use Dimensity/Dimensity-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Dimensity/Dimensity-3B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Dimensity/Dimensity-3B", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Dimensity/Dimensity-3B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Dimensity/Dimensity-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Dimensity/Dimensity-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Dimensity/Dimensity-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Dimensity/Dimensity-3B

SGLang

How to use Dimensity/Dimensity-3B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Dimensity/Dimensity-3B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Dimensity/Dimensity-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Dimensity/Dimensity-3B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Dimensity/Dimensity-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Dimensity/Dimensity-3B with Docker Model Runner:
```
docker model run hf.co/Dimensity/Dimensity-3B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Dimensity-3B

Model Details

Dimensity-3B is a finetuned version of the StableLM framework trained on a variety of conversational data. It contains 3 billion parameters.

Intended Uses

This model is intended for conversational AI applications. It can engage in open-ended dialogue by generating responses to user prompts.

Factors

Training Data

The model was trained on a large dataset of over 100 million conversational exchanges extracted from Reddit comments, customer support logs, and other online dialogues.

Prompt Template

The model was finetuned using the following prompt template:

### Human: {prompt} 

### Assistant:

This prompts the model to take on an assistant role.

Ethical Considerations

As the model was trained on public conversational data, it may generate responses that contain harmful stereotypes or toxic content. The model should be used with caution in sensitive contexts.

Caveats and Recommendations

This model is designed for open-ended conversation. It may sometimes generate plausible-sounding but incorrect information. Outputs should be validated against external sources.

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