Open royallavanya140 opened 6 days ago
Problem is that you can't batch forward passes with different LoRA settings. Applying a LoRA effectively changes the weights of the model. It's a temporary change via a low-rank overlay, but it's still effectively the same as swapping out the model for a different one. Which makes sense as long as there aren't any requests in the queue, but while requests are processing, I don't know how the framework should interpret that..?
OS
Linux
GPU Library
CUDA 12.x
Python version
3.12
Pytorch version
2.3.1
Model
mistral-v0.3-instruct
Describe the bug
i hosted llm using fastapi and accept the lora weights from the users but If I receive the weights when the model is bsy in generation. is there any way to edit the weights without disturbing current generation.
Reproduction steps
Expected behavior
LoRAs cannot be updated while there are jobs in the generator queue
Logs
No response
Additional context
No response
Acknowledgements