| #!/usr/bin/env bash |
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| set -e |
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| TOKEN="${HF_TOKEN:-}" |
| MAX_STEPS="${MAX_STEPS:-100000}" |
| BATCH_SIZE="${BATCH_SIZE:-4}" |
| GRAD_ACCUM="${GRAD_ACCUM:-8}" |
| SEQ_LEN="${SEQ_LEN:-512}" |
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| echo "" |
| echo "╔════════════════════════════════════════════════╗" |
| echo "║ CogNet-1B — SSH Launcher ║" |
| echo "╚════════════════════════════════════════════════╝" |
| echo "" |
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| if [ ! -f "train_ultra.py" ]; then |
| echo "[1/5] Cloning CogNet-1B..." |
| git clone https://huggingface.co/thefinalboss/CogNet-1B cognet-1b 2>/dev/null || true |
| cd cognet-1b |
| echo " Cloné dans $(pwd)" |
| else |
| echo "[1/5] Déjà dans le repo: $(pwd)" |
| fi |
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| echo "" |
| echo "[2/5] Installation des dépendances..." |
| pip install -q torch datasets huggingface_hub tokenizers 2>/dev/null || pip install torch datasets huggingface_hub tokenizers |
| echo " OK" |
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| echo "" |
| echo "[3/5] Vérification GPU..." |
| if command -v nvidia-smi &>/dev/null; then |
| GPU_COUNT=$(nvidia-smi --query-gpu=name --format=csv,noheader 2>/dev/null | wc -l) |
| GPU_NAME=$(nvidia-smi --query-gpu=name --format=csv,noheader 2>/dev/null | head -1) |
| VRAM=$(nvidia-smi --query-gpu=memory.total --format=csv,noheader,nounits 2>/dev/null | head -1) |
| echo " GPU: ${GPU_COUNT}x ${GPU_NAME} (${VRAM}MB)" |
| else |
| GPU_COUNT=0 |
| echo " ATTENTION: Pas de GPU détecté — training sur CPU (lent!)" |
| fi |
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| echo "" |
| echo "[4/5] HuggingFace token..." |
| if [ -z "$TOKEN" ]; then |
| echo " NON DÉFINI — export HF_TOKEN=hf_xxx avant de lancer" |
| echo " Le data download HF peut échouer sans token" |
| else |
| echo " OK: ${TOKEN:0:8}..." |
| export HF_TOKEN="$TOKEN" |
| fi |
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| echo "" |
| echo "[5/5] Lancement du training..." |
| echo " max_steps=${MAX_STEPS} batch=${BATCH_SIZE} grad_accum=${GRAD_ACCUM} seq_len=${SEQ_LEN}" |
| echo "" |
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| export COGNET_WORKSPACE="$(pwd)" |
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| if [ "$GPU_COUNT" -gt 1 ]; then |
| echo " Multi-GPU détecté → torchrun avec ${GPU_COUNT} GPUs" |
| python -m torch.distributed.run \ |
| --standalone \ |
| --nproc_per_node="$GPU_COUNT" \ |
| train_ultra.py \ |
| --max-steps "$MAX_STEPS" \ |
| --batch-size "$BATCH_SIZE" \ |
| --grad-accum "$GRAD_ACCUM" \ |
| --seq-len "$SEQ_LEN" \ |
| --use-fsdp \ |
| --compile \ |
| --cuda-prefetch \ |
| --seq-warmup \ |
| --async-ckpt |
| else |
| echo " Single GPU/CPU → python direct" |
| python train_ultra.py \ |
| --max-steps "$MAX_STEPS" \ |
| --batch-size "$BATCH_SIZE" \ |
| --grad-accum "$GRAD_ACCUM" \ |
| --seq-len "$SEQ_LEN" \ |
| --compile \ |
| --cuda-prefetch \ |
| --seq-warmup \ |
| --async-ckpt |
| fi |
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