flash feature refactor #778
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This PR extends the Qwen2 architecture to other models other than `Alibaba-NLP/gte-Qwen2-7B-instruct`, given that the prior implementation was only covering such cases so as to use causal attention on CUDA and to rely on the provided tokenizer rather than patching it. # What does this PR do? - makes flash-attn-3 and flash-attn-cpu easier to add. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/text-embeddings-inference/blob/main/CONTRIBUTING.md)? - [ ] Was this discussed/approved via a GitHub issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs). - [ ] Did you write any new necessary tests? If applicable, did you include or update the `insta` snapshots? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @Narsil OR @alvarobartt -->
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This PR extends the Qwen2 architecture to other models other than
Alibaba-NLP/gte-Qwen2-7B-instruct, given that the prior implementation was only covering such cases so as to use causal attention on CUDA and to rely on the provided tokenizer rather than patching it.What does this PR do?
Fixes # (issue)
Before submitting
instasnapshots?Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.