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 DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bb1070/cfb_fp8_torchao", torch_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
- Xet hash:
- 214e0c77fb696d21343658ba27089e4c9427f5079a04551d3d02a5afb3ed48b3
- Size of remote file:
- 246 MB
- SHA256:
- 9a081df38a9b16e94853cdd53dc89f3c9115b06afffc979a680d32037d987972
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