Instructions to use BiliSakura/BitDance-Tokenizer-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/BitDance-Tokenizer-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/BitDance-Tokenizer-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download bitdance_diffusers/__main__.py from BiliSakura/BitDance-Tokenizer-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 66 Bytes
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https://huggingface.co/BiliSakura/BitDance-Tokenizer-diffusers/resolve/main/bitdance_diffusers/__main__.py
- Command line
-
hf download hf://BiliSakura/BitDance-Tokenizer-diffusers/bitdance_diffusers/__main__.py
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curl -L -o __main__.py https://huggingface.co/BiliSakura/BitDance-Tokenizer-diffusers/resolve/main/bitdance_diffusers/__main__.py
66 Bytes
| from .convert import main | |
| if __name__ == "__main__": | |
| main() | |