Download auto-impl/scripts/ptb_probes.sbatch from Jerry999/RSIChallenge: direct link, hf CLI and curl.
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https://huggingface.co/datasets/Jerry999/RSIChallenge/resolve/main/auto-impl/scripts/ptb_probes.sbatch
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hf download hf://datasets/Jerry999/RSIChallenge/auto-impl/scripts/ptb_probes.sbatch
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2.84 kB
| #!/bin/bash | |
| # Score the four PostTrainBench base models on the offline capability probes. | |
| # | |
| # sbatch --array=0-3 scripts/ptb_probes.sbatch | |
| # | |
| # One array task per model, one GPU each: the probes are a few thousand short | |
| # log-likelihood passes, so this is minutes of compute once the weights load. | |
| # | |
| # Scored under both pmi and letter. Plain mean-token-logprob ("norm") is | |
| # deliberately not the default: a positive control showed it collapses onto | |
| # whichever option has the highest unconditional likelihood, putting even a | |
| # 27B instruct model below chance. | |
| # Results land in analysis/out/probe_results/<model>.json; summarise them with | |
| # python analysis/summarize_probes.py | |
| # OUT_TAG suffixes the filename. Set it for any re-run that scores fewer | |
| # probes or fewer schemes than the file already there, or the narrower run | |
| # silently replaces a broader one: | |
| # OUT_TAG=_variants SCORING=pmi VARIANTS=base,swap sbatch --array=0-3 ... | |
| #SBATCH --job-name=ptb-probes | |
| #SBATCH --partition=h100 | |
| #SBATCH --account=midpri | |
| #SBATCH --qos=midpri | |
| #SBATCH --gres=gpu:1 | |
| #SBATCH --cpus-per-task=12 | |
| #SBATCH --mem=128G | |
| #SBATCH --time=01:00:00 | |
| #SBATCH --output=logs/ptb-probes-%A_%a.out | |
| set -euo pipefail | |
| # The login pod's proxy is not routable from a compute node, and an inherited | |
| # http_proxy makes every HF call hang before falling back to the local cache. | |
| unset http_proxy https_proxy HTTP_PROXY HTTPS_PROXY no_proxy NO_PROXY X2P_PROXY_URL | |
| REPO=/home/jiaruiliu/local/git-repos/auto-impl | |
| cd "$REPO" | |
| export HF_HOME=/lustre-storage/fsx_2/user/jiaruiliu/ptb-data/hf_cache | |
| export HF_HUB_OFFLINE=1 TRANSFORMERS_OFFLINE=1 HF_DATASETS_OFFLINE=1 | |
| export TOKENIZERS_PARALLELISM=false | |
| # A compile cache shared across concurrent engines on one node triggers an | |
| # Errno 116 storm on Lustre; the judge pool learned this the hard way. | |
| export VLLM_CACHE_ROOT="/tmp/vllm-cache-${SLURM_JOB_ID}-${SLURM_ARRAY_TASK_ID:-0}" | |
| mkdir -p "$VLLM_CACHE_ROOT" | |
| MODELS=( | |
| "Qwen/Qwen3-4B-Base" | |
| "Qwen/Qwen3-1.7B-Base" | |
| "HuggingFaceTB/SmolLM3-3B-Base" | |
| "google/gemma-3-4b-pt" | |
| ) | |
| REPO_ID="${MODELS[${SLURM_ARRAY_TASK_ID:-0}]}" | |
| NAME="${REPO_ID//\//__}" | |
| # Resolve the local snapshot rather than passing the repo id: offline mode | |
| # still consults the hub index for a bare id and fails on some layouts. | |
| SNAP=$(ls -d "$HF_HOME/hub/models--${REPO_ID//\//--}/snapshots/"*/ 2>/dev/null | head -1) | |
| if [[ -z "$SNAP" ]]; then | |
| echo "No local snapshot for $REPO_ID under $HF_HOME/hub" >&2 | |
| exit 1 | |
| fi | |
| echo "model=$REPO_ID snapshot=$SNAP" | |
| nvidia-smi -L | |
| "$HOME/.venv-vllm-serve/bin/python" analysis/run_probes.py \ | |
| --model "$SNAP" \ | |
| --name "$REPO_ID" \ | |
| --out "analysis/out/probe_results/${NAME}${OUT_TAG:-}.json" \ | |
| --max-model-len "${MAX_MODEL_LEN:-4096}" \ | |
| --gpu-util "${GPU_UTIL:-0.85}" \ | |
| --scoring "${SCORING:-pmi,letter}" \ | |
| --variants "${VARIANTS:-base}" | |