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 inference_config.json from TencentARC/WorldCrafter-Fast: direct link, hf CLI and curl.
- Browser
- Download file 419 Bytes
-
https://huggingface.co/TencentARC/WorldCrafter-Fast/resolve/main/inference_config.json
- Command line
-
hf download hf://TencentARC/WorldCrafter-Fast/inference_config.json
-
curl -L -o inference_config.json https://huggingface.co/TencentARC/WorldCrafter-Fast/resolve/main/inference_config.json
419 Bytes
| { | |
| "format": "worldcrafter_fast_v1", | |
| "shared_components": ".", | |
| "routing": [ | |
| [ | |
| "equal", | |
| "equal" | |
| ], | |
| [ | |
| "equal", | |
| "equal" | |
| ], | |
| [ | |
| "equal", | |
| "old" | |
| ] | |
| ], | |
| "steps_per_stage": [ | |
| 2, | |
| 2, | |
| 2 | |
| ], | |
| "guidance_scale": 1.0, | |
| "ucpe_pixel_center": true, | |
| "repencoder_target_microbatch": 1, | |
| "representation": "resident_byte_compact_ucpe", | |
| "compile": false | |
| } | |