sayakpaul/diffusers-torchao
End-to-end recipes for optimizing diffusion models with torchao and diffusers (inference and FP8 training).
Combines `torch.compile()` with `torchao`'s quantization schemes (INT8, FP8) to accelerate diffusion model inference, achieving 53.88% speedup on Flux.1-Dev and 27.33% on CogVideoX-5b. Provides end-to-end recipes for both inference optimization and experimental FP8 training, with serialization strategies to reduce framework overhead. Integrates directly into the Hugging Face `diffusers` pipeline as an official quantization backend, supporting automatic quantization (`autoquant`) with minimal code changes.
397 stars.
Stars
397
Forks
16
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 08, 2026
Commits (30d)
0
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