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
| 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 $(date -u) exit=$? ===" | |