Datasets:
Update README.md
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README.md
CHANGED
@@ -7,6 +7,85 @@ This dataset was created by automatically translating "OpenAssistant/oasst1" int
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The "ng_translation" flag indicates that the translation was not successful, and "1" means that the translation failed.
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Therefore, for data with "1", "text" and "text_en" contain the same text.
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oasst1-ja-89k Repository
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https://github.com/kunishou/oasst1-89k-ja
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The "ng_translation" flag indicates that the translation was not successful, and "1" means that the translation failed.
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Therefore, for data with "1", "text" and "text_en" contain the same text.
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以下のコードを用いることで、 Instruction と Output (prompterの命令とassistantの回答)の形式に変換することができます。
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ファインチューニングで使用する場合はこちらのコードで変換して下さい。
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変換コード参考
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https://github.com/h2oai/h2o-llmstudio/blob/5ebfd3879e226b4e1afd0a0b45eb632e60412129/app_utils/utils.py#L1888
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```python
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pip install huggingface-hub
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pip install datasets
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```
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```python
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from datasets import load_dataset
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import pandas as pd
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import os
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import json
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# oasst1のオリジナルデータのロード
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ds = load_dataset("OpenAssistant/oasst1")
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train = ds["train"].to_pandas()
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val = ds["validation"].to_pandas()
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df_origin = pd.concat([train, val], axis=0).reset_index(drop=True)
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# oasst1日本語翻訳データの読み込み
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df_ja = pd.read_json("oasst1_ja_89k.json")
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# oasst1のオリジナルデータと日本語翻訳データのマージ
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df = pd.merge(df_origin, df_ja[["message_id", "text_ja"]], on="message_id", how="left").copy()
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df["text"] = df["text_ja"]
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df_assistant = df[(df.role == "assistant")].copy()
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df_prompter = df[(df.role == "prompter")].copy()
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df_prompter = df_prompter.set_index("message_id")
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df_assistant["output"] = df_assistant["text"].values
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inputs = []
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parent_ids = []
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for _, row in df_assistant.iterrows():
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input = df_prompter.loc[row.parent_id]
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inputs.append(input.text)
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parent_ids.append(input.parent_id)
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df_assistant["instruction"] = inputs
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df_assistant["parent_id"] = parent_ids
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df_assistant = df_assistant[
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["instruction", "output", "message_id", "parent_id", "lang", "rank"]
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].rename(columns={"message_id": "id"})
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# 翻訳タスクのみデータに異常があるので除外
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df_assistant2 = df_assistant[~df_assistant["instruction"].str.contains("翻訳")]
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# これ以下でjsonファイルへ書き出し---------------
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learn_datas = []
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input_list = []
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for n in range(len(df_assistant2)):
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learn_data = {
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"instruction": str(df_assistant2.iloc[n, 0]),
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"input": "",
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"output": ""
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}
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input_list.append(df_assistant2.iloc[n, 0])
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learn_data["input"] = ""
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learn_data["output"] = str(df_assistant2.iloc[n, 1])
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learn_datas.append(learn_data)
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json_learn_data = json.dumps(learn_datas, indent=4, ensure_ascii=False)
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with open('oasst1_ja_51k_converted.json', 'w', encoding="utf-8") as f:
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f.write(json_learn_data)
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```
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oasst1-ja-89k Repository
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https://github.com/kunishou/oasst1-89k-ja
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