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Title: GitHub - yangw-dev/ao: PyTorch native quantization and sparsity for training and inference

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sam-fasthttps://pytorch.org/blog/accelerating-generative-ai
gpt-fasthttps://pytorch.org/blog/accelerating-generative-ai-2
sd-fasthttps://pytorch.org/blog/accelerating-generative-ai-3
up to 1.5x speedupshttps://pytorch.org/blog/training-using-float8-fsdp2/
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Float8 in PyTorchhttps://dev-discuss.pytorch.org/t/float8-in-pytorch-1-x/1815
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Keynote talk at GPU MODE IRLhttps://youtu.be/FH5wiwOyPX4?si=VZK22hHz25GRzBG1&t=1009
Low precision dtypes at PyTorch conferencehttps://youtu.be/xcKwEZ77Cps?si=7BS6cXMGgYtFlnrA
Slaying OOMs at the Mastering LLM's coursehttps://www.youtube.com/watch?v=UvRl4ansfCg
Advanced Quantization at CUDA MODEhttps://youtu.be/1u9xUK3G4VM?si=4JcPlw2w8chPXW8J
Chip Huyen's GPU Optimization Workshophttps://www.youtube.com/live/v_q2JTIqE20?si=mf7HeZ63rS-uYpS6
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2:4 Sparse Marlin GEMMhttps://github.com/pytorch/ao/pull/733
int4 tinygemm unpackerhttps://github.com/pytorch/ao/pull/415
this issuehttps://github.com/pytorch/ao/issues/697
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