Instructions to use ChengYangYang/bpp-reading-pointer-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ChengYangYang/bpp-reading-pointer-weights with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ChengYangYang/bpp-reading-pointer-weights", 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 earlier_lines/keyframe_ckpt/frames.pt from ChengYangYang/bpp-reading-pointer-weights: direct link, hf CLI and curl.
- Browser
- Download file 142 MB
-
https://huggingface.co/ChengYangYang/bpp-reading-pointer-weights/resolve/main/earlier_lines/keyframe_ckpt/frames.pt
- Command line
-
hf download hf://ChengYangYang/bpp-reading-pointer-weights/earlier_lines/keyframe_ckpt/frames.pt
-
curl -L -o frames.pt https://huggingface.co/ChengYangYang/bpp-reading-pointer-weights/resolve/main/earlier_lines/keyframe_ckpt/frames.pt
142 MB
- Xet hash:
- 024e09214a44e5af7e7f5e92ef9c60924228a882bea92b3d32c4500f67977d79
- Size of remote file:
- 142 MB
- SHA256:
- 6f92b425df8534a6a5084cfff80c72df5be128c7fdb8e0a7d2df453b4e37a4d5
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