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
File size: 423 Bytes
3be3ec6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | 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",
]
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