[online trainers] add vllm lora adapter support #4590
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| if self.vllm_use_lora: | ||
| # Cycle through 2 adapter IDs to force vLLM to reload updated weights while keeping memory usage bounded | ||
| # vLLM uses lora_int_id as the cache key (see WorkerLoRAManager.add_adapter) | ||
| # By alternating between 2 IDs, we ensure the adapter is reloaded each step without accumulating N adapters |
| if self.vllm_use_lora: | ||
| import tempfile | ||
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| # Create a temporary directory to save the LoRA adapter (only once) |
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any edge case in case it's training on a distributed/multi-node setup?
kashif
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Could you explain the context of this PR? In my understanding, if you use LoRA for vLLM the generation is expected to be slower. Why not just merging the adapter before the training? |
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