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[Llama4] Enable attention temperature tuning by default for long context (>32k) #16439
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[Llama4] Enable attention temperature tuning by default for long context (>32k) #16439
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Signed-off-by: Ye (Charlotte) Qi <[email protected]>
Signed-off-by: Ye (Charlotte) Qi <[email protected]>
👋 Hi! Thank you for contributing to the vLLM project. 💬 Join our developer Slack at https://slack.vllm.ai to discuss your PR in #pr-reviews, coordinate on features in #feat- channels, or join special interest groups in #sig- channels. Just a reminder: PRs would not trigger full CI run by default. Instead, it would only run Once the PR is approved and ready to go, your PR reviewer(s) can run CI to test the changes comprehensively before merging. To run CI, PR reviewers can either: Add 🚀 |
we probably need to update blog accordingly and tell users how to disable instead lol also cc: @astonzhang |
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Thanks for all the evals!
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Looks good, thanks!
Since we auto-enable this with max-model-len > 32 in PR vllm-project/vllm#16439, this tip can be removed to avoid confusion.
Since we auto-enable this with max-model-len > 32 in PR vllm-project/vllm#16439, this tip can be removed to avoid confusion.
…ext (>32k) (vllm-project#16439) Signed-off-by: Ye (Charlotte) Qi <[email protected]> Co-authored-by: Ye (Charlotte) Qi <[email protected]> Signed-off-by: Yang Wang <[email protected]>
…ext (>32k) (vllm-project#16439) Signed-off-by: Ye (Charlotte) Qi <[email protected]> Co-authored-by: Ye (Charlotte) Qi <[email protected]>
…ext (>32k) (vllm-project#16439) Signed-off-by: Ye (Charlotte) Qi <[email protected]> Co-authored-by: Ye (Charlotte) Qi <[email protected]>
…ext (>32k) (vllm-project#16439) Signed-off-by: Ye (Charlotte) Qi <[email protected]> Co-authored-by: Ye (Charlotte) Qi <[email protected]> Signed-off-by: Mu Huai <[email protected]>
Attention temperature tuning (on nope layers) improves accuracy on long context (>32k) tasks. Enabling it by default for long context unless explicitly disabled by the user.
Eval results on RULER with and without attention temperature tuning (@luccafong):
cc: @ywang96 @simon-mo @DarkLight1337