Added documentation of using warmups to initialize lora weights

triton-inference-server / tensorrtllm_backend

The Triton TensorRT-LLM Backend

Apache License 2.0

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Added documentation of using warmups to initialize lora weights #515

Open TheCodeWrangler opened 3 months ago

TheCodeWrangler commented 3 months ago

This PR provides documentation for converting lora adapters from a hugging face checkpoint into a warmup that can be used in the triton-inference-server TensorRT-LLM backend.

This approach allows for the LoRa weights to never be required for the client of the triton-inference-server backend and does not require loading or passing these weights from any of the python backend models (preprocessing) to avoid the numpy datatype conversion (which does not support bfloat16)

smehta2000 commented 2 months ago

Tagging @kaiyux @byshiue to help triage and/or add to review board, thanks!

TheCodeWrangler commented 1 month ago

Curious to get any feedback here

This update is also related to a performance issue I am seeing.
https://github.com/NVIDIA/TensorRT-LLM/issues/1957

This PR gets results much closer to the expected outputs but not fully in line with huggingface/ pre-compiled results. Would love to have some feedback on the process for preparation of the adapter weights.