Instructions to use TencentARC/WorldCrafter-Fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TencentARC/WorldCrafter-Fast with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TencentARC/WorldCrafter-Fast", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Download model_index.json from TencentARC/WorldCrafter-Fast: direct link, hf CLI and curl.
- Browser
- Download file 1.75 kB
-
https://huggingface.co/TencentARC/WorldCrafter-Fast/resolve/main/model_index.json
- Command line
-
hf download hf://TencentARC/WorldCrafter-Fast/model_index.json
-
curl -L -o model_index.json https://huggingface.co/TencentARC/WorldCrafter-Fast/resolve/main/model_index.json
1.75 kB
| { | |
| "_class_name": "WorldCrafter", | |
| "_module": "worldcrafter", | |
| "_format": "worldcrafter_fast_model_index_v1", | |
| "_diffusers_version": "0.37.0", | |
| "_loading": { | |
| "entrypoint": "worldcrafter.WorldCrafter.from_pretrained", | |
| "model_type": "fast", | |
| "requires_custom_loader": true, | |
| "inference_config": "inference_config.json", | |
| "manifest": "manifest.json" | |
| }, | |
| "_pipeline": { | |
| "library": "worldcrafter", | |
| "class_name": "WorldCrafterPipeline", | |
| "is_distilled": true | |
| }, | |
| "transformer_high_noise": [ | |
| "worldcrafter", | |
| "WorldCrafterTransformer3DModel" | |
| ], | |
| "transformer_low_noise": [ | |
| "worldcrafter", | |
| "WorldCrafterTransformer3DModel" | |
| ], | |
| "repencoder": [ | |
| "worldcrafter", | |
| "RepEncoder" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "UMT5EncoderModel" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "T5TokenizerFast" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKLWan" | |
| ], | |
| "scheduler": [ | |
| "worldcrafter", | |
| "WorldCrafterScheduler" | |
| ], | |
| "_adapters": { | |
| "high_noise": { | |
| "transformer": "transformer_high_noise", | |
| "lora_weights": "adapter_high_noise/pytorch_lora_weights.safetensors", | |
| "camera_weights": "adapter_high_noise/transformer_partial.pth", | |
| "timestep_contract": "adapter_high_noise/dmd_timestep_contract.json", | |
| "repencoder_reference": "adapter_high_noise/repencoder_frozen.json" | |
| }, | |
| "low_noise": { | |
| "transformer": "transformer_low_noise", | |
| "lora_weights": "adapter_low_noise/pytorch_lora_weights.safetensors", | |
| "camera_weights": "adapter_low_noise/transformer_partial.pth", | |
| "timestep_contract": "adapter_low_noise/dmd_timestep_contract.json", | |
| "repencoder_reference": "adapter_low_noise/repencoder_frozen.json" | |
| } | |
| } | |
| } | |