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
| from .constants import SUPPORTED_IMAGE_SIZES | |
| from .modeling_autoencoder import BitDanceAutoencoder | |
| from .modeling_diffusion_head import BitDanceDiffusionHead | |
| from .modeling_projector import BitDanceProjector | |
| from .pipeline_bitdance import BitDanceDiffusionPipeline | |
| __all__ = [ | |
| "SUPPORTED_IMAGE_SIZES", | |
| "BitDanceAutoencoder", | |
| "BitDanceDiffusionHead", | |
| "BitDanceProjector", | |
| "BitDanceDiffusionPipeline", | |
| ] | |