| append_example.py | 3.94 kB | | dcff21a6 |
| audit_converted_solutions.py | 4.24 kB | | 44e18894 |
| audit_dataset_quality.py | 4.44 kB | | f76cda37 |
| audit_sft_messages.py | 6.5 kB | | f50c797d |
| audit_sft_templates.py | 9.08 kB | | 16475b65 |
| build_clean_training_set.py | 2.55 kB | | 9f375b6c |
| build_sft_messages.py | 12.5 kB | | 69275b67 |
| convert_raw_ideas.py | 18.1 kB | | 57a9a212 |
| dataset_quality_utils.py | 14.8 kB | | cc3a4b14 |
| filter_sft_quality.py | 4.37 kB | | 4b3b7eae |
| find_best_repos.py | 26.9 kB | | d0d8cd7f |
| gen_bedimcode_50.py | 87 kB | | 1b950daa |
| gen_bedimcode_restaurant_100.py | 122 kB | | c1078332 |
| generate_code_output_correction_rows.py | 32.8 kB | | e99b5904 |
| generate_game_repo_rows.py | 27.5 kB | | 61c8830a |
| mythos_lora_core.py | 8.72 kB | | 9e178511 |
| preview_code_output_examples.py | 4.47 kB | | 4e2afd21 |
| repair_weak_rows.py | 9.25 kB | | 6b2d0b96 |
| run_quality_pipeline.py | 6.06 kB | | acf30b81 |
| run_validation.py | 2.48 kB | | 729dfe80 |
| runpod_setup_check.py | 2.9 kB | | 96288ae4 |
| score_dataset.py | 7.53 kB | | d1375287 |
| sft_pipeline_utils.py | 5.26 kB | | b89a2216 |
| split_dataset.py | 5.17 kB | | 3124587b |
| test_lora_model.py | 2.52 kB | | 32ea1bbe |
| train_lora_sft.py | 2.7 kB | | add947a8 |
| validate_jsonl.py | 5.46 kB | | 0a3d1304 |
