Instructions to use bb1070/cfb_fp8_torchao with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bb1070/cfb_fp8_torchao with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import FluxFillPipeline from diffusers.utils import load_image image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png") mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png") # switch to "mps" for apple devices pipe = FluxFillPipeline.from_pretrained("bb1070/cfb_fp8_torchao", dtype=torch.bfloat16, device_map="cuda") image = pipe( prompt="a white paper cup", image=image, mask_image=mask, height=1632, width=1232, guidance_scale=30, num_inference_steps=50, max_sequence_length=512, generator=torch.Generator("cpu").manual_seed(0) ).images[0] image.save(f"flux-fill-dev.png") - Notebooks
- Google Colab
- Kaggle
Download text_encoder/pytorch_model.bin from bb1070/cfb_fp8_torchao: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/bb1070/cfb_fp8_torchao/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://bb1070/cfb_fp8_torchao/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bb1070/cfb_fp8_torchao/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 214e0c77fb696d21343658ba27089e4c9427f5079a04551d3d02a5afb3ed48b3
- Size of remote file:
- 246 MB
- SHA256:
- 9a081df38a9b16e94853cdd53dc89f3c9115b06afffc979a680d32037d987972
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