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danieldk 
posted an update 7 days ago
sayakpaul 
authored a paper 2 months ago
sayakpaul 
submitted a paper to Daily Papers 2 months ago
sayakpaul 
authored 4 papers 4 months ago
sayakpaul 
submitted a paper to Daily Papers 4 months ago
danieldk 
posted an update 4 months ago
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We have recently added Torch Stable ABI support to kernels and kernel-builder. This allows kernel developers to target a particular Torch version and the kernel will be supported on that Torch version and later Torch versions (up to ~2 years).

This makes it much easier to write kernels with long-term support and not just the last two Torch releases.

We have also started rolling out Stable ABI support to kernels in kernels-community, starting with Flash Attention 3, supporting Torch 2.9 and later as well as CUDA versions starting at 12.6:

https://huggingface.co/kernels/kernels-community/flash-attn3/tree/v1/build
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sayakpaul 
updated a Space 5 months ago
sayakpaul 
published a Space 5 months ago
danieldk 
posted an update 6 months ago
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299
Two large changes in kernel-builder this week:

kernel-builder now links libstdc++ dynamically. To support a wide range of systems, we build against libstdc++ from manylinux_2_28 (EL 8 and later).

Following our Torch support policy that the current and previous Torch versions are supported, Torch 2.10 support was removed. We will soon also support the Torch stable ABI, so that it is possible to write kernels that support a large number of Torch versions.
sayakpaul 
authored 2 papers 8 months ago
sayakpaul 
submitted a paper to Daily Papers 8 months ago
sayakpaul 
authored a paper 9 months ago
danieldk 
posted an update 9 months ago
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kernels 0.12 is out! 🎉

Changes:

* Support for kernel version branches to gracefully roll out kernel API changes.
* Support for PyTorch 2.10.
* kernel-builder is now merged into the kernels repo.
* Initial support for standardized kernel benchmarks.

https://github.com/huggingface/kernels/releases/tag/v0.12.0
danieldk 
posted an update about 1 year ago
sayakpaul 
authored a paper about 1 year ago
sayakpaul 
posted an update over 1 year ago
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Fast LoRA inference for Flux with Diffusers and PEFT 🚨

There are great materials that demonstrate how to optimize inference for popular image generation models, such as Flux. However, very few cover how to serve LoRAs fast, despite LoRAs being an inseparable part of their adoption.

In our latest post, @BenjaminB and I show different techniques to optimize LoRA inference for the Flux family of models for image generation. Our recipe includes the use of:

1. torch.compile
2. Flash Attention 3 (when compatible)
3. Dynamic FP8 weight quantization (when compatible)
4. Hotswapping for avoiding recompilation during swapping new LoRAs 🤯

We have tested our recipe with Flux.1-Dev on both H100 and RTX 4090. We achieve at least a *2x speedup* in either of the GPUs. We believe our recipe is grounded in the reality of how LoRA-based use cases are generally served. So, we hope this will be beneficial to the community 🤗

Even though our recipe was tested primarily with NVIDIA GPUs, it should also work with AMD GPUs.

Learn the details and the full code here:
https://huggingface.co/blog/lora-fast
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