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/boundary_reader/reader.pt from ChengYangYang/bpp-reading-pointer-weights: direct link, hf CLI and curl.
- Browser
- Download file 4.21 MB
-
https://huggingface.co/ChengYangYang/bpp-reading-pointer-weights/resolve/main/earlier_lines/boundary_reader/reader.pt
- Command line
-
hf download hf://ChengYangYang/bpp-reading-pointer-weights/earlier_lines/boundary_reader/reader.pt
-
curl -L -o reader.pt https://huggingface.co/ChengYangYang/bpp-reading-pointer-weights/resolve/main/earlier_lines/boundary_reader/reader.pt
4.21 MB
- Xet hash:
- 2295b676af67d95ea8f9660c7940d1a54c0f8cc9e1f89e30b2ff365c7ba3d3cc
- Size of remote file:
- 4.21 MB
- SHA256:
- 049aec37c2bc15e5efba16efa8e8d63d8f443a72ee6126bcd6c0a74f81ca8c46
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.