Unconditional Image Generation
Diffusers
Safetensors
English
bitdance
imagenet
class-conditional
custom-pipeline
Instructions to use BiliSakura/BitDance-ImageNet-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/BitDance-ImageNet-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/BitDance-ImageNet-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download BitDance_B_16x/bitdance_imagenet_diffusers/__init__.py from BiliSakura/BitDance-ImageNet-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 306 Bytes
-
https://huggingface.co/BiliSakura/BitDance-ImageNet-diffusers/resolve/main/BitDance_B_16x/bitdance_imagenet_diffusers/__init__.py
- Command line
-
hf download hf://BiliSakura/BitDance-ImageNet-diffusers/BitDance_B_16x/bitdance_imagenet_diffusers/__init__.py
-
curl -L -o __init__.py https://huggingface.co/BiliSakura/BitDance-ImageNet-diffusers/resolve/main/BitDance_B_16x/bitdance_imagenet_diffusers/__init__.py
306 Bytes
| from .modeling_autoencoder import BitDanceImageNetAutoencoder | |
| from .modeling_transformer import BitDanceImageNetTransformer | |
| from .pipeline_bitdance_imagenet import BitDanceImageNetPipeline | |
| __all__ = [ | |
| "BitDanceImageNetAutoencoder", | |
| "BitDanceImageNetTransformer", | |
| "BitDanceImageNetPipeline", | |
| ] | |