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01ikedachin /imabari_wiki_qa_v4_validated_w_reasoning_effort_qwen38 Imabari Wiki QA v4 Validated with Reasoning Effort — Qwen3.8 概要 / Overview 日本語・今治弁のQAを用いて、reasoning effort に応じた思考文の生成を学習するための教師ありファインチューニング(SFT)用データセットです。Imabari Wiki QA v4 Validated の質問と回答を保持し、元記事の文脈を参照して思考文を再生成しています。 This dataset supports supervised fine-tuning (SFT) of reasoning-effort-conditioned explanations using Japanese QA with Imabari dialect expressions. Questions and answers from Imabari Wiki QA v4 Validated are preserved, while reasoning text is… See the full description on the dataset page: https://huggingface.co/datasets/ikedachin/imabari_wiki_qa_v4_validated_w_reasoning_effort_qwen38.textquestion-answering10K<n<100K0 likes138 downloads8d agoHugging Face02ikedachin /imabari_wiki_qa_v4_reasoning_effort_llmjp4 Imabari Wiki QA v4 with Reasoning Effort — LLM-jp 4 概要 / Overview 日本語・今治弁のQAを用いて、reasoning effort に応じた思考文の生成を学習するための教師ありファインチューニング(SFT)用データセットです。Imabari Wiki QA v4 Validated の質問と回答を保持し、元記事の文脈を参照して思考文を再生成しています。 This dataset supports supervised fine-tuning (SFT) of reasoning-effort-conditioned explanations using Japanese QA with Imabari dialect expressions. Questions and answers from Imabari Wiki QA v4 Validated are preserved, while reasoning text is regenerated… See the full description on the dataset page: https://huggingface.co/datasets/ikedachin/imabari_wiki_qa_v4_reasoning_effort_llmjp4.textquestion-answering10K<n<100K0 likes137 downloads8d agoHugging Face03ikedachin /imabari_wiki_qa_v4_reasoning_effort_qwen38 Imabari Wiki QA v4 with Reasoning Effort — Qwen3.8 概要 / Overview 日本語・今治弁のQAを用いて、reasoning effort に応じた思考文の生成を学習するための教師ありファインチューニング(SFT)用データセットです。Imabari Wiki QA v4 Validated の質問と回答を保持し、元記事の文脈を参照して思考文を再生成しています。 This dataset supports supervised fine-tuning (SFT) of reasoning-effort-conditioned explanations using Japanese QA with Imabari dialect expressions. Questions and answers from Imabari Wiki QA v4 Validated are preserved, while reasoning text is regenerated with… See the full description on the dataset page: https://huggingface.co/datasets/ikedachin/imabari_wiki_qa_v4_reasoning_effort_qwen38.textquestion-answering10K<n<100K0 likes89 downloads8d agoHugging Face04NotEvilAI /ru-reasoning_effort-sft_dpo_think_gpt NotEvilAI/ru-reasoning_effort-sft_dpo_think_gpt NotEvilAI/ru-reasoning_effort-sft_dpo_think_gpt - синтетический датасет для поддержки генерации ризонинга на русском языке с вариативным объёмом thinking(reasoning_effort). Reasoning_effort представлен в виде системного промта Reasoning: [effort], где effort - одно из следующих значений: low, medium, high - стандартные значения минимального, среднего и большого ризонинга для gpt-oss-20b/gpt-oss-120b none - отключить ризонинг, в… See the full description on the dataset page: https://huggingface.co/datasets/NotEvilAI/ru-reasoning_effort-sft_dpo_think_gpt.tabulartext-generation100K<n<1M3 likes84 downloads1y agoHugging Face05ikedachin /std_lang_wiki_qa_v4_validated_w_reasoning_effort_llmjp4 Standard Japanese Wiki QA v4 with Reasoning Effort — LLM-jp 4 概要 Imabari Wiki QA v4 with Reasoning Effort — LLM-jp 4 の thinking(思考文)と answer(最終回答)の言葉遣いを標準語(です・ます調)へ変換した派生データセットです。日本語QAの教師ありファインチューニング(SFT)や、reasoning effort に応じた説明文・回答の生成に利用できます。 質問に新たに回答したり、推論内容を追加したりすることは目的としていません。元の意味・結論・根拠を保持し、今治弁などの方言表現を標準語へ置き換えるよう指示しています。質問は変換対象に含めていません。 LLM-jp 4 のチャットテンプレート用に、assistant の content に最終回答、thinking に思考文を格納しています。「LLM-jp 4」は対象のデータ形式を示します。元の思考文生成モデルと標準語化の設定モデルは… See the full description on the dataset page: https://huggingface.co/datasets/ikedachin/std_lang_wiki_qa_v4_validated_w_reasoning_effort_llmjp4.textquestion-answering10K<n<100K0 likes66 downloads4d agoHugging Face06valendra /sherry-reasoning-effort-0.1-dataset Sherry Reasoning Effort Dataset (0.1) Math reasoning traces at 3 effort levels (low, medium, high) generated by Qwen3.6-35B-A3B (NVFP4) via API. Description Each problem was sampled from NuminaMath-CoT (numeric-answer problems only, proofs filtered out). For every problem, 3 candidates were sampled from the generator model with thinking enabled, verified against the ground truth, and the 3 verified traces with different reasoning depths were kept: the shortest… See the full description on the dataset page: https://huggingface.co/datasets/valendra/sherry-reasoning-effort-0.1-dataset.texttext-generation1K<n<10K0 likes53 downloads18d agoHugging Face

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