Instructions to use mignonjia/hyworld with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mignonjia/hyworld 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("mignonjia/hyworld", 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 feature_extractor/preprocessor_config.json from mignonjia/hyworld: direct link, hf CLI and curl.
- Browser
- Download file 394 Bytes
-
https://huggingface.co/mignonjia/hyworld/resolve/main/feature_extractor/preprocessor_config.json
- Command line
-
hf download hf://mignonjia/hyworld/feature_extractor/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/mignonjia/hyworld/resolve/main/feature_extractor/preprocessor_config.json
394 Bytes
| { | |
| "do_convert_rgb": null, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "SiglipImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "SiglipProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 384, | |
| "width": 384 | |
| } | |
| } | |