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@rahul-tuli rahul-tuli commented May 2, 2025

This PR updates the main README.md to introduce a "New Features" section, improving visibility for recent major additions to LLM Compressor.

This section highlights:

Signed-off-by: Rahul Tuli <[email protected]>
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👋 Hi! Thank you for contributing to llm-compressor. Please add the ready label when the PR is ready for review.

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@rahul-tuli rahul-tuli self-assigned this May 2, 2025
@rahul-tuli rahul-tuli marked this pull request as ready for review May 2, 2025 13:56
Signed-off-by: Rahul Tuli <[email protected]>
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I would formalize the tone a little bit here.

Axolotl only supports one modifier atm (iirc),

I would also avoid using words like "our", since this is an open source community project.

- Meta utilized LLM Compressor to create the
+ See the FP8-quantized Llama-4-Maverick-17B-128E model created using LLM Compressor by the Meta AI team

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I would formalize the tone a little bit here.

Axolotl only supports one modifier atm (iirc),

I would also avoid using words like "our", since this is an open source community project.

- Meta utilized LLM Compressor to create the
+ See the FP8-quantized Llama-4-Maverick-17B-128E model created using LLM Compressor by the Meta AI team
  • I think the sentence reads okay;
  • I removed our and linked out to compressed-tensors.
  • w.r.t > Axolotl only supports one modifier atm (iirc),
    Which is all we need for Sparse Finetuning 👀

@rahul-tuli rahul-tuli added the ready When a PR is ready for review label May 2, 2025
@rahul-tuli rahul-tuli enabled auto-merge (squash) May 2, 2025 17:16
@rahul-tuli rahul-tuli merged commit 7bc1881 into main May 2, 2025
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@rahul-tuli rahul-tuli deleted the add-new-features-section branch May 2, 2025 17:45
kylesayrs pushed a commit that referenced this pull request May 4, 2025
This PR updates the main README.md to introduce a "New Features"
section, improving visibility for recent major additions to LLM
Compressor.

This section highlights:

- Axolotl Sparse Finetuning Integration
(https://docs.axolotl.ai/docs/custom_integrations.html#llmcompressor)
- AutoAWQ Integration for low-bit weight quantization (#1177)
- Day 0 Llama 4 support and its use by Meta
This helps users quickly understand the latest capabilities of the
library.

---------

Signed-off-by: Rahul Tuli <[email protected]>
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