Instructions to use MagicCard/msrh-zindi-magic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MagicCard/msrh-zindi-magic with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
| #!/usr/bin/env python3 | |
| '''Build v8 variants of K=7 fewshot train + test by replacing v1 prefix with v8. | |
| v8 = shortened v6 anchored-extraction (33 words vs v6 70 words). | |
| ''' | |
| import json, pathlib | |
| V1 = 'Use the retrieved contexts as your primary sources — copy exact phrasing where the contexts already address the question. Be concise and factually accurate.' | |
| V8 = 'The retrieved contexts are your source of truth — copy or paraphrase their exact phrasing to answer. Reply in the same language and script as the question. Plain prose, no disclaimers or meta-commentary.' | |
| DATA_DIR = pathlib.Path('/mnt/msrh/Magic_submission/LF/data') | |
| PAIRS = [ | |
| ('msrh_rag_train_afrie5_TV_k7_fewshot.json', 'msrh_rag_train_afrie5_TV_k7_fewshot_v8.json'), | |
| ('msrh_rag_test_k3_AfriE5_TV_fewshot_k7.json', 'msrh_rag_test_k3_AfriE5_TV_fewshot_k7_v8.json'), | |
| ] | |
| for src_name, dst_name in PAIRS: | |
| src = DATA_DIR / src_name | |
| dst = DATA_DIR / dst_name | |
| n_ok = n_miss = 0 | |
| with open(src) as fin, open(dst, 'w') as fout: | |
| for ln in fin: | |
| r = json.loads(ln) | |
| c = r['messages'][0]['content'] | |
| if V1 in c: | |
| r['messages'][0]['content'] = c.replace(V1, V8) | |
| n_ok += 1 | |
| else: | |
| n_miss += 1 | |
| fout.write(json.dumps(r, ensure_ascii=False) + '\n') | |
| print(f'{src_name:55s} -> {dst_name:55s} ok={n_ok} miss={n_miss}') | |