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| Task | Shots | Metric | Score |
|---|---|---|---|
| HellaSwag | 0 | acc_norm | 25.39% |
| LAMBADA OpenAI | 0 | acc | 0.10% |
| PIQA | 0 | acc_norm | 49.78% |
| WinoGrande | 0 | acc | 49.80% |
| ARC-Easy | 0 | acc_norm | 24.83% |
| ARC-Challenge | 0 | acc_norm | 26.11% |
| BoolQ | 0 | acc | 37.83% |
| MMLU（57科目平均） | 0 | acc | 23.02% |
| 全タスク平均 | - | - | 29.61% |
trust_remote_code=True が必要です。KVキャッシュ非対応のため use_cache=False で生成してください。1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model = AutoModelForCausalLM.from_pretrained(
4 "Ryosei-Akatsuka/kopriaLM", trust_remote_code=True)
5tok = AutoTokenizer.from_pretrained("Ryosei-Akatsuka/kopriaLM")
6
7ids = tok("Q: What is 2+2?\nA: ", return_tensors="pt")
8gen = model.generate(**ids, max_new_tokens=30, use_cache=False)
9print(tok.decode(gen[0], skip_special_tokens=True))