madcat
53 lines
1.8 KiB
Makefile
53 lines
1.8 KiB
Makefile
venv := "/home/madcat/lora-train"
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data := "bt7274_v2.jsonl"
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# Train LoRA adapter (stop vLLM first if running)
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train:
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@echo "── BT-7274 LoRA training ──"
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@test -f {{data}} || (echo "MISSING: {{data}}" && exit 1)
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@echo "Data: {{data}} ($(wc -l < {{data}}) examples)"
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@echo "Activating venv: {{venv}}"
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bash -c 'source {{venv}}/bin/activate && python train.py'
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# Dry run — load data, print stats, exit
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check:
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bash -c 'source {{venv}}/bin/activate && python -c "\
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from datasets import load_dataset; \
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ds = load_dataset(\"json\", data_files=\"{{data}}\", split=\"train\"); \
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print(f\"Examples: {len(ds)}\"); \
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roles = {}; \
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[roles.update({r: roles.get(r,0)+1}) for ex in ds for m in ex[\"messages\"] for r in [m[\"role\"]]]; \
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print(f\"Roles: {roles}\"); \
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lens = [sum(len(m.get(\"content\",\"\") or \"\") for m in ex[\"messages\"]) for ex in ds]; \
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print(f\"Avg chars/example: {sum(lens)//len(lens)}\"); \
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print(f\"Max chars/example: {max(lens)}\"); \
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"'
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# Stop vLLM server (frees GPU for training)
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stop-vllm:
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-pkill -f "vllm.entrypoints"
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@echo "vLLM stopped"
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# Start vLLM server with v2 adapter
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serve:
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bash ~/start-vllm.sh
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# Start vLLM with v2 adapter override
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serve-v2:
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@echo "Starting vLLM with v2 adapter..."
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bash -c 'source /home/madcat/vllm-serve/bin/activate && \
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python -m vllm.entrypoints.openai.api_server \
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--model Qwen/Qwen2.5-7B-Instruct \
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--quantization bitsandbytes \
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--load-format bitsandbytes \
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--enable-lora \
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--lora-modules bt7274=/home/madcat/Projects/lora/bt7274-lora-v2 \
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--max-lora-rank 16 \
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--max-model-len 32768 \
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--enforce-eager \
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--enable-auto-tool-choice \
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--tool-call-parser hermes \
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--port 8000 \
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> /home/madcat/vllm-bt7274.log 2>&1 &'
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@echo "vLLM started (log: ~/vllm-bt7274.log)"
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