Download auto-impl/scripts/ptb_probe_control.sbatch from Jerry999/RSIChallenge: direct link, hf CLI and curl.
- Browser
- Download file 1.96 kB
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https://huggingface.co/datasets/Jerry999/RSIChallenge/resolve/main/auto-impl/scripts/ptb_probe_control.sbatch
- Command line
-
hf download hf://datasets/Jerry999/RSIChallenge/auto-impl/scripts/ptb_probe_control.sbatch
-
curl -L -o ptb_probe_control.sbatch https://huggingface.co/datasets/Jerry999/RSIChallenge/resolve/main/auto-impl/scripts/ptb_probe_control.sbatch
1.96 kB
| # The positive control for the capability probes: a model that unquestionably | |
| # has the capability being asked about, run through the identical pipeline. | |
| # | |
| # sbatch scripts/ptb_probe_control.sbatch | |
| # VARIANTS=base,neutral2,swap,reworded sbatch scripts/ptb_probe_control.sbatch | |
| # | |
| # This exists because a probe can fail for two reasons -- the model cannot do | |
| # it, or the question is broken -- and only a control separates them. It has | |
| # already earned its keep twice: it retired P1 v1 (the control scored 0.0945 | |
| # on an 8-way choice with a 0.394 majority line) and it validated P2 (0.883 | |
| # balanced against a 0.855 trivial policy). Run it before believing any | |
| # number a base model produces. | |
| # | |
| # Qwen3.6-27B-instruct, the same weights the judge pool serves, at TP=2. | |
| #SBATCH --job-name=ptb-probe-ctrl | |
| #SBATCH --partition=h100 | |
| #SBATCH --account=midpri | |
| #SBATCH --qos=midpri | |
| #SBATCH --gres=gpu:2 | |
| #SBATCH --cpus-per-task=24 | |
| #SBATCH --mem=256G | |
| #SBATCH --time=02:00:00 | |
| #SBATCH --output=logs/ptb-probe-ctrl-%j.out | |
| set -euo pipefail | |
| 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 "$REPO" | |
| export HF_HOME=/lustre-storage/fsx_2/user/jiaruiliu/ptb-data/hf_cache | |
| export HF_HUB_OFFLINE=1 TRANSFORMERS_OFFLINE=1 HF_DATASETS_OFFLINE=1 | |
| export TOKENIZERS_PARALLELISM=false | |
| export VLLM_CACHE_ROOT="/tmp/vllm-cache-ctrl-${SLURM_JOB_ID}" | |
| mkdir -p "$VLLM_CACHE_ROOT" | |
| MODEL_PATH="${MODEL_PATH:-/lustre-storage/fsx_0/checkpoints/Qwen3.6-27B}" | |
| OUT="${OUT:-analysis/out/probe_results/_control_Qwen3.6-27B_${TAG:-v3}.json}" | |
| nvidia-smi -L | |
| "$HOME/.venv-vllm-serve/bin/python" analysis/run_probes.py \ | |
| --model "$MODEL_PATH" \ | |
| --name "CONTROL-Qwen3.6-27B-instruct" \ | |
| --out "$OUT" \ | |
| --max-model-len "${MAX_MODEL_LEN:-4096}" \ | |
| --gpu-util "${GPU_UTIL:-0.90}" \ | |
| --tensor-parallel "${TP:-2}" \ | |
| --scoring "${SCORING:-pmi,letter}" \ | |
| --variants "${VARIANTS:-base}" | |