Instructions to use fusing/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fusing/test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fusing/test", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| { | |
| "_name_or_path": "xlm-roberta-large", | |
| "architectures": [ | |
| "RobertaSeriesModelWithTransformation" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "layer_norm_eps": 1e-05, | |
| "learn_encoder": false, | |
| "max_position_embeddings": 514, | |
| "model_type": "xlm-roberta", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "output_past": true, | |
| "pad_token_id": 1, | |
| "pooler_fn": "cls", | |
| "position_embedding_type": "absolute", | |
| "project_dim": 768, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.24.0", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 250002 | |
| } | |