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#!/bin/bash
#SBATCH --job-name=sft_qlora
#SBATCH --output=sft_qlora_%j.out
#SBATCH --error=sft_qlora_%j.err
#SBATCH --time=12:00:00
#SBATCH --partition=a100
#SBATCH --gres=gpu:1
#SBATCH --cpus-per-task=8
#SBATCH --mem=64G
# QLoRA SFT Training - Ultra Minimal Hardware (1 GPU, ~12GB VRAM)
# Can run on A100 40GB, V100, or even consumer GPUs
cd /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/collaborativeagents/training
source /u/yurenh2/miniforge3/etc/profile.d/conda.sh
conda activate eval
echo "=== Starting QLoRA SFT Training ==="
echo "GPU: $(nvidia-smi --query-gpu=name --format=csv,noheader | head -1)"
echo "Config: llama_factory_qlora_config.yaml"
echo "Start time: $(date)"
# Run training with LLaMA-Factory
llamafactory-cli train llama_factory_qlora_config.yaml
echo "=== Training Complete ==="
echo "End time: $(date)"
echo "Output: outputs/sft_reflection_qlora"
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