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| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA |
|---|---|---|---|---|---|
| meta-llama/Llama-2-13b-hf | 56.9 | 58.11 | 80.97 | 54.34 | 34.17 |
| meta-llama/Llama-2-13b-chat-hf | 59.93 | 59.04 | 81.94 | 54.64 | 44.12 |
| ehartford/dolphin-llama-13b | 59.26 | 55.55 | 77.11 | 52.16 | 52.23 |
| CHIH-HUNG/llama-2-13b-dolphin_20w | 60.17 | 59.56 | 82.55 | 55.89 | 42.67 |
| CHIH-HUNG/llama-2-13b-dolphin_5w | 61 | 60.67 | 82.69 | 56.23 | 44.41 |
1import json
2from datasets import load_dataset
3
4# 讀取數據集,take可以取得該數據集前n筆資料
5dataset = load_dataset("ehartford/dolphin", split="train", streaming=True).take(50000)
6
7# 提取所需欄位並建立新的字典列表
8extracted_data = []
9for example in dataset:
10 extracted_example = {
11 ### dolphin
12 "instruction": example["instruction"],
13 "input": example["input"],
14 "output": example["output"]
15 }
16 extracted_data.append(extracted_example)
17
18# 指定 JSON 文件名稱
19json_filename = "dolphin.json"
20
21# 寫入 JSON 文件
22with open(json_filename, "w") as json_file:
23 json.dump(extracted_data, json_file, indent=4)
24
25print(f"數據已提取並保存為 {json_filename}")