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Running on A10G
Running on A10G
File size: 3,180 Bytes
95cbc5b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 | #!/usr/bin/env bash
# =============================================================================
# CommitGuard — GCP VM Setup Script
# Target: GCE VM with NVIDIA L4 (24 GB) or A100 (40/80 GB)
# =============================================================================
set -euo pipefail
echo "============================================"
echo " CommitGuard GCP Training VM Setup"
echo "============================================"
# --- 1. System packages ---
sudo apt-get update -qq
sudo apt-get install -y -qq git python3-venv python3-pip tmux htop
# --- 2. NVIDIA driver check ---
if ! command -v nvidia-smi &>/dev/null; then
echo "ERROR: nvidia-smi not found. Use a GCP image with pre-installed GPU drivers:"
echo " - Deep Learning VM (recommended)"
echo " - Or install manually: sudo apt install nvidia-driver-535"
exit 1
fi
echo "GPU detected:"
nvidia-smi --query-gpu=name,memory.total --format=csv,noheader
# --- 3. Clone repo ---
REPO_DIR="$HOME/commitguard"
if [ ! -d "$REPO_DIR" ]; then
echo "Cloning repo..."
git clone https://github.com/NitishKumar-ai/commitguard.git "$REPO_DIR"
else
echo "Repo exists, pulling latest..."
cd "$REPO_DIR" && git pull
fi
cd "$REPO_DIR"
# --- 4. Python venv ---
if [ ! -d ".venv" ]; then
python3 -m venv .venv
fi
source .venv/bin/activate
pip install -U pip setuptools wheel -q
# --- 5. Install training dependencies ---
echo "Installing training dependencies..."
pip install -e . -q
pip install \
"torch>=2.4" \
"unsloth[cu124-torch240]" \
"trl>=0.12" \
"peft>=0.13" \
"bitsandbytes>=0.44" \
"transformers>=4.46" \
"datasets>=3.0" \
"accelerate>=1.0" \
"wandb" \
"requests" \
"matplotlib" \
"jupyter" \
"ipywidgets" \
-q
echo "Verifying installs..."
python -c "
import torch, trl, unsloth, peft, wandb, bitsandbytes
print(f'PyTorch: {torch.__version__}')
print(f'CUDA: {torch.cuda.is_available()} — {torch.cuda.get_device_name(0) if torch.cuda.is_available() else \"N/A\"}')
print(f'TRL: {trl.__version__}')
print(f'PEFT: {peft.__version__}')
print(f'Wandb: {wandb.__version__}')
print('All training deps OK.')
"
echo ""
echo "============================================"
echo " Setup complete. Two options to train:"
echo "============================================"
echo ""
echo " ── OPTION A: Jupyter Notebook (recommended) ──"
echo ""
echo " # On the VM:"
echo " cd $REPO_DIR && source .venv/bin/activate"
echo " tmux new -s server -d 'source .venv/bin/activate && server'"
echo " jupyter notebook --no-browser --port=8888 --ip=0.0.0.0"
echo ""
echo " # On your LOCAL machine (new terminal):"
echo " gcloud compute ssh commitguard-train --zone=us-central1-a -- -NL 8888:localhost:8888"
echo ""
echo " # Then open in browser:"
echo " # http://localhost:8888 → notebooks/train_commitguard.ipynb"
echo ""
echo " ── OPTION B: CLI ──"
echo ""
echo " cd $REPO_DIR && source .venv/bin/activate"
echo " tmux new -s server -d 'source .venv/bin/activate && server'"
echo " huggingface-cli login"
echo " python scripts/train_grpo.py --samples 200 --max-steps 300"
echo ""
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