e893795443
[2/N] executor pass the complete config to worker/modelrunner ( #9938 )
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Signed-off-by: youkaichao <youkaichao@gmail.com >
Co-authored-by: Nick Hill <nhill@redhat.com >
2024-11-02 07:35:05 -07:00
Jee Jee Li and GitHub
a48e3ec052
[CI/Build][LoRA] Temporarily fix long context failure issue ( #9579 )
2024-10-22 11:32:51 +00:00
42c7f66a38
[Core] Support dynamically loading Lora adapter from HuggingFace ( #6234 )
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Co-authored-by: Antoni Baum <antoni.baum@protonmail.com >
2024-07-22 15:42:40 -07:00
4d6ada947c
[CORE] Adding support for insertion of soft-tuned prompts ( #4645 )
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Co-authored-by: Swapnil Parekh <swapnilp@ibm.com >
Co-authored-by: Joe G <joseph.granados@h2o.ai >
Co-authored-by: Antoni Baum <antoni.baum@protonmail.com >
2024-07-09 13:26:36 -07:00
Cyrus Leung and GitHub
0e9164b40a
[mypy] Enable type checking for test directory ( #5017 )
2024-06-15 04:45:31 +00:00
Antoni Baum and GitHub
ccdc490dda
[Core] Change LoRA embedding sharding to support loading methods ( #5038 )
2024-06-06 19:07:57 -07:00
5ae5ed1e60
[Core] Consolidate prompt arguments to LLM engines ( #4328 )
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Co-authored-by: Roger Wang <ywang@roblox.com >
2024-05-28 13:29:31 -07:00
SangBin Cho and GitHub
2e9a2227ec
[Lora] Support long context lora ( #4787 )
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Currently we need to call rotary embedding kernel for each LoRA, which makes it hard to serve multiple long context length LoRA. Add batched rotary embedding kernel and pipe it through.
It replaces the rotary embedding layer to the one that is aware of multiple cos-sin-cache per scaling factors.
Follow up of https://github.com/vllm-project/vllm/pull/3095/files
2024-05-18 16:05:23 +09:00
