Seth
48b627d498
- training/scripts/train_lora.py: Unsloth QLoRA trainer for qwen3:8b - training/scripts/train_lora.sh: Launch script for steel141 RTX 3090 Ti - eval/bakeoff.py: Fixed token budget (400->1500) that caused qwen3 models to exhaust tokens on thinking, added --no-think flag - agent/serve.py: Default model changed to gemma3n:e4b Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
32 lines
795 B
Bash
Executable File
32 lines
795 B
Bash
Executable File
#!/usr/bin/env bash
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# LoRA fine-tuning launcher for qwen3:8b on steel141
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#
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# Prerequisites (already installed):
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# conda activate mc-train (or use full path below)
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# Python 3.11, PyTorch 2.10+cu124, Unsloth 2026.3.5
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#
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# Usage:
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# ssh steel141
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# cd ~/mc-ai-training
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# bash train_lora.sh
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#
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# Or from CT 629:
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# ssh steel141 "cd ~/mc-ai-training && bash train_lora.sh"
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set -euo pipefail
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PYTHON=~/miniconda3/envs/mc-train/bin/python
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SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
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# Use RTX 3090 Ti (GPU 0 in PyTorch ordering)
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export CUDA_VISIBLE_DEVICES=0
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echo "=== Minecraft AI LoRA Training ==="
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echo "Python: $($PYTHON --version)"
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echo "GPU: RTX 3090 Ti (24GB)"
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echo "Base model: Qwen/Qwen3-8B"
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echo "Dataset: seed_dataset.jsonl"
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echo ""
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exec $PYTHON "$SCRIPT_DIR/train_lora.py" "$@"
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