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Tested and looks great! |
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This was referenced Oct 16, 2024
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@Ying1123 @merrymercy python3 -m sglang.launch_server --model-path /base_model --tokenizer-path /base_model --lora-paths /lora_model0 /lora_model1 --disable-radix --disable-cuda-graph --max-loras-per-batch 2 --mem-fraction-static 0.5 --random-seed 0 --enable-torch-compileAttributeError: 'Gemma2ForCausalLM' object has no attribute 'get_module_name' Related issues: #1416 Resolved PR: #2330 (comment) |
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@Ying1123 Does this feature support multimodal models such as Qwen2-VL? Currently vLLM does not support this. |
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This PR gives initial multi-LoRA serving support. Currently, it supports LoRA on attention (
qkvo) and mlp (gate, up, down) linear layers. It supports dynamic loading and offloading, but it does not support unified memory. The memory pool for LoRA adapters is pre-allocated. Please use a smaller--mem-fracto launch server with larger--max-loras-per-batch.Current example usage:
You can expect the items below in the follow-up PRs.
References:
S-LoRA: Serving Thousands of Concurrent LoRA Adapters
Punica: Multi-Tenant LoRA Serving