# Model weights (67G)
/models
/.claude

# --- Large generated artifacts -------------------------------------------
# Raw attention dumps from 2-2 step 01 (~25GB, 80 files x ~360MB).
# Intermediate only: consumed by Ident_IH_02_score.py to build
# head_scoring_combined.json. Regenerate with Ident_IH_ALL_1-4_<model>.sh.
*.pkl

# 2-3 threshold sweep results (~690MB). Regenerate with
# Ident_H_01_EvaluateInstructiveHead_gpu0.sh.
/Codes/2-2_head_identification_scoring/model_score/*/heads_sorted_eval/

# LoRA adapters / checkpoints from 3-2 training (~3.2GB).
/Codes/3-2_model_training/outputs_lora/
/Codes/3-2_model_training/test_outputs/
/Codes/3-2_model_training/len_test_outputs/

# 4-1 evaluation outputs
/Codes/4-1_evaluation_single/results/

# NOTE: model_score/*/heads_sorted/ and head_scoring_combined.json are kept on
# purpose -- they are small (~5MB) and are the HEAD_PATH inputs that stage 3-2
# depends on, so tracking them avoids a GPU rerun of 2-2 after a fresh clone.

# --- Python / editor cruft ------------------------------------------------
__pycache__/
*.py[cod]
.ipynb_checkpoints/