Instructions to use TencentARC/WorldCrafter-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TencentARC/WorldCrafter-Base 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-Base", 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 adapter/config.json from TencentARC/WorldCrafter-Base: direct link, hf CLI and curl.
- Browser
- Download file 186 Bytes
-
https://huggingface.co/TencentARC/WorldCrafter-Base/resolve/main/adapter/config.json
- Command line
-
hf download hf://TencentARC/WorldCrafter-Base/adapter/config.json
-
curl -L -o config.json https://huggingface.co/TencentARC/WorldCrafter-Base/resolve/main/adapter/config.json
186 Bytes
| { | |
| "adaptation_method": "parallel", | |
| "attention_compression": 8, | |
| "camera_condition": "relray_absmap", | |
| "format": "worldcrafter_adapter_v1", | |
| "resolution": [ | |
| 384, | |
| 640 | |
| ] | |
| } | |