Reinforcement Learning
PEFT
Safetensors
reward-hacking
model-organism
grpo
activation-oracle
AVBench
Instructions to use cds-jb/qwen3-8b-overwrite-tests-rh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cds-jb/qwen3-8b-overwrite-tests-rh with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 842 Bytes
e106e01 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | #!/bin/bash
cd /workspace/rl-rewardhacking
export PATH="$HOME/.local/bin:$PATH"
export GIT_REPO_NAME=rl-rewardhacking
set -a; source .env.gpu; source .env; set +a
source "$VENV_DIR/bin/activate"
export VLLM_ATTENTION_BACKEND=FLASH_ATTN VLLM_USE_FLASHINFER_SAMPLER=0 VLLM_WORKER_MULTIPROC_METHOD=spawn
CKPT="results/runs/qwen3-8b/20260614_221419_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_aware_baseline/checkpoints/global_step_200"
echo "=== EVAL START $(date -u) | ckpt=$CKPT ==="
uv run --active --no-sync scripts/run_eval.py run \
--model_id=Qwen/Qwen3-8B \
--lora_adapter_path="$CKPT" \
--dataset_path=results/data/leetcode_test_medhard_simple_overwrite_tests_aware.jsonl \
--n_samples=10 --max_new_tokens=1536 --max_prompt_length=1536 \
--overwrite=True
echo "=== EVAL FINISHED $(date -u) exit=$? ==="
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