Enable hybrid attention models for Transformers backend (#18494)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-05-23 04:12:08 +02:00
committed by GitHub
parent c6b636f9fb
commit 4b0da7b60e
4 changed files with 106 additions and 30 deletions

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@ -117,7 +117,7 @@ For models with interleaving sliding windows (e.g. `google/gemma-2-2b-it` and `m
To support a model with interleaving sliding windows, we need to take care of the following details:
- Make sure [this line](https://github.com/vllm-project/vllm/blob/996357e4808ca5eab97d4c97c7d25b3073f46aab/vllm/config.py#L308) evaluates `has_interleaved_attention` to `True` for this model, and set `self.hf_text_config.interleaved_sliding_window` to the format of interleaving sliding windows the model can understand. Then, `self.hf_text_config.sliding_window` will be deleted, and the model will be treated as a full-attention model.
- Make sure the model's `config.json` contains `sliding_window_pattern`. vLLM then sets `self.hf_text_config.interleaved_sliding_window` to the value of `self.hf_text_config.sliding_window` and deletes `sliding_window` from `self.hf_text_config`. The model will then be treated as a full-attention model.
- In the modeling code, parse the correct sliding window value for every layer, and pass it to the attention layer's `per_layer_sliding_window` argument. For reference, check [this line](https://github.com/vllm-project/vllm/blob/996357e4808ca5eab97d4c97c7d25b3073f46aab/vllm/model_executor/models/llama.py#L171).
With these two steps, interleave sliding windows should work with the model.