datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
llm-jp-4-thinking-sft-data
llm-jp-4-thinking-sft-data
Overview
This dataset is a supervised fine-tuning (SFT) dataset used to train llm-jp-4-*-thinking models.
This dataset is constructed by extracting prompts from multiple data sources and generating reasoning processes and final responses using gpt-oss-120b.
The splits reasoning_low, reasoning_medium, and reasoning_high correspond to different reasoning effort settings used during generation with gpt-oss-120b.
To support the continued development… See the full description on the dataset page: https://huggingface.co/datasets/llm-jp/llm-jp-4-thinking-sft-data.UltraData-SFT-2605-no-think-8k-32k
UltraData-SFT-2605 · no_think · 8k–32k
A length-filtered subset of the no_think split of
openbmb/UltraData-SFT-2605,
containing conversations whose token length falls in the 8k–32k range.
This is the medium-length tier intended for standard long-context SFT.
Two companion tiers were produced from the same source:
Dataset
Length range
Records
this repo — fxmeng/UltraData-SFT-2605-no-think-8k-32k
8k–32k tokens
623,421
fxmeng/UltraData-SFT-2605-no-think-32k-200k… See the full description on the dataset page: https://huggingface.co/datasets/fxmeng/UltraData-SFT-2605-no-think-8k-32k.Dolci-Think-SFT-32B
Dolci-Think-SFT
Sources include a mixture of existing reasoning traces:
OpenThoughts 3 (Apache 2.0): Extended to 32K context length and downsampled code prompts to 16X multiple, to 941,164 total prompts. Access our version, Dolci OpenThoughts 3 here.
SYNTHETIC-2 (Apache 2.0) via the SFT-Verified split, 104,568 prompts.
Nemotron Post-training dataset (CC BY 4), code split only, 113,777 prompts.
New prompts and new reasoning traces from us (all ODC-BY-1.0):
Dolci Think Persona IF:… See the full description on the dataset page: https://huggingface.co/datasets/allenai/Dolci-Think-SFT-32B.Dolci-Think-SFT-7B
Dolci-Think-SFT
Sources include a mixture of existing reasoning traces:
OpenThoughts 3 (Apache 2.0): Extended to 32K context length and downsampled code prompts to 16X multiple, to 941,166 total prompts. Access our version, Dolci OpenThoughts 3 here.
SYNTHETIC-2 (Apache 2.0) via the SFT-Verified split, 104,569 prompts.
Nemotron Post-training dataset (CC BY 4), code split only, 113,777 prompts.
New prompts and new reasoning traces from us (all ODC-BY-1.0):
Dolci Think Persona… See the full description on the dataset page: https://huggingface.co/datasets/allenai/Dolci-Think-SFT-7B.Dolci-Think-SFT-32B-Multilingual
Dolci-Think-SFT-32B-Multilingual
Dolci-Think-SFT-32B-Multilingual is a large-scale multilingual long chain-of-thought (CoT) reasoning corpus spanning six languages: English, French, German, Spanish, Chinese, and Swahili. Each sample includes a question, a long-form reasoning trace, and a final answer, all translated into the target language, with sequences up to 32,768 tokens.
It is released alongside the paper Rethinking the Multilingual Reasoning Gap with Layer Swap.… See the full description on the dataset page: https://huggingface.co/datasets/lightonai/Dolci-Think-SFT-32B-Multilingual.MMFineReason-SFT-586K-Qwen3-VL-235B-Thinking
MMFineReason-SFT-586K
The Hardest 33% — Less Data, More Reasoning
📖 Overview
MMFineReason-SFT-586K is a difficulty-filtered subset of MMFineReason-1.8M, containing the hardest 33% of samples where Qwen3-VL-4B-Thinking do not consistently succeed. (pass rate ≠ 1).
Specifically, this subset removes all easy samples (pass rate = 1) under Qwen3-VL-4B-Thinking, retaining only instances that require non-trivial multimodal reasoning.
🎯 Key Highlights
586K… See the full description on the dataset page: https://huggingface.co/datasets/OpenDataArena/MMFineReason-SFT-586K-Qwen3-VL-235B-Thinking.Dolci-Think-SFT-PythonThis dataset is licensed under ODC-BY. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines.
Citation
@misc{olmo2025olmo3,
title={Olmo 3},
author={Team Olmo and Allyson Ettinger and Amanda Bertsch and Bailey Kuehl and David Graham and David Heineman and Dirk Groeneveld and Faeze Brahman and Finbarr Timbers and Hamish Ivison and Jacob Morrison and Jake Poznanski and Kyle Lo and Luca Soldaini and Matt Jordan and Mayee Chen and Michael… See the full description on the dataset page: https://huggingface.co/datasets/allenai/Dolci-Think-SFT-Python.UltraData-SFT-2605-no-think-32k-200k
UltraData-SFT-2605 · no_think · 32k–200k
A length-filtered subset of the no_think split of
openbmb/UltraData-SFT-2605,
containing conversations whose token length falls in the 32k–200k range.
This is the long-context tier intended for extended-context SFT.
Two companion tiers were produced from the same source:
Dataset
Length range
Records
fxmeng/UltraData-SFT-2605-no-think-8k-32k
8k–32k tokens
623,421
this repo — fxmeng/UltraData-SFT-2605-no-think-32k-200k
32k–200k… See the full description on the dataset page: https://huggingface.co/datasets/fxmeng/UltraData-SFT-2605-no-think-32k-200k.Dolci-Think-SFT-translated
Dolci-Think-SFT-translated
Machine translations of the Dolci-Think-SFT-32B dataset, produced with gemma-4-31B-it. The samples selected for translation are those where content_quality == "excellent" according to the propella annotations.
Columns
Each row is a translated conversation plus the result of a post-translation quality filter:
id — source record id.
messages — the translated conversation (list of {content, role}).
filter_pass — true if the row passed… See the full description on the dataset page: https://huggingface.co/datasets/openeurollm/Dolci-Think-SFT-translated.Dolci-Think-SFT-Olmo-Hybrid
Licensing Information
Dolci Think SFT Olmo Hybrid is licensed under the Open Data Commons Attribution License v1.0 (ODC-By). It is intended for research and educational use. For more information, please see our Responsible Use Guidelines.
Dolci-Think-SFT-7B-multiturnSoofi-Think-SFT-10B-multilingual
ReasonXL: A Multilingual Cross-Domain Reasoning Corpus
ReasonXL is a large-scale multilingual reasoning corpus spanning 5 languages and ~44B tokens in total. It is designed to support supervised fine-tuning of reasoning models with in-language chain-of-thought traces across diverse technical domains.
Data Generation
English source samples were drawn from 10 existing reasoning datasets, filtered and quality-annotated using ellamind/propella-1-4b, and then translated into… See the full description on the dataset page: https://huggingface.co/datasets/toroe/Soofi-Think-SFT-10B-multilingual.llm-jp-4-thinking-sft-data-chatmlllm-jpのデータセットllm-jp-4-thinking-sft-dataを、
ChatML形式に変換したものです。
ライセンス
各サンプルのライセンスは、元データセットカードに記載された各データソースのライセンスに従います。
本リポジトリは、元となったデータ全体に対して新たなライセンスを付与するものではありません。
利用する場合は、対応する元データソースのライセンス条件を確認してください。
MMFineReason-SFT-123K-Qwen3-VL-235B-Thinking
MMFineReason-SFT-123K
The Hardest 7% — Less Data, More Reasoning
📖 Overview
MMFineReason-SFT-123K is a difficulty-filtered subset of MMFineReason-1.8M, containing only the hardest 7% of samples where Qwen3-VL-4B-Thinking consistently fails (pass rate = 0).
🎯 Key Highlights
123K Challenging Samples: Only instances where a 4B thinking model fails all 4 inference attemptsEfficient Training: Comparable performance to full 1.8M dataset with only 7% of… See the full description on the dataset page: https://huggingface.co/datasets/OpenDataArena/MMFineReason-SFT-123K-Qwen3-VL-235B-Thinking.Dolci-Think-SFT-7B-decontaminated
Decontamination
This dataset is a decontaminated version of allenai/Dolci-Think-SFT-7B.
Benchmarks used
MATH500: HuggingFaceH4/MATH-500 (subset=default, split=test)
AIME24: HuggingFaceH4/aime_2024 (subset=default, split=train)
AIME25: math-ai/aime25 (subset=default, split=test)
AMC23: math-ai/amc23 (subset=default, split=test)
JEEBench: daman1209arora/jeebench (subset=default, split=test)
GPQADiamond: Idavidrein/gpqa (subset=gpqa_diamond, split=train)… See the full description on the dataset page: https://huggingface.co/datasets/openeurollm/Dolci-Think-SFT-7B-decontaminated.Dolci-Think-SFT-32B-decontaminated
Decontamination
This dataset is a decontaminated version of allenai/Dolci-Think-SFT-32B.
Benchmarks used
MATH500: HuggingFaceH4/MATH-500 (subset=default, split=test)
AIME24: HuggingFaceH4/aime_2024 (subset=default, split=train)
AIME25: math-ai/aime25 (subset=default, split=test)
AMC23: math-ai/amc23 (subset=default, split=test)
JEEBench: daman1209arora/jeebench (subset=default, split=test)
GPQADiamond: Idavidrein/gpqa (subset=gpqa_diamond, split=train)… See the full description on the dataset page: https://huggingface.co/datasets/openeurollm/Dolci-Think-SFT-32B-decontaminated.clean-gsm8k-aug-gpt2-0.1b-lora-think-sft-ar-clean-gsm8k-aug
clean-gsm8k-aug-gpt2-0.1b-lora-think-sft-ar-clean-gsm8k-aug
Ten generated think-sft-ar responses per question from cs-giung/gpt2-0.1b-lora-think-sft-ar-clean-gsm8k-aug (revision step-300000), generated on 2026-08-07.
Schema
Field
Type
Meaning
question
str
Source question from cs-giung/clean-gsm8k-aug
steps
list[list[str]]
The 10 responses, each split into reasoning steps
answer
list[str]
The 10 per-response answer blocks
Every record has… See the full description on the dataset page: https://huggingface.co/datasets/cs-giung/clean-gsm8k-aug-gpt2-0.1b-lora-think-sft-ar-clean-gsm8k-aug.dolci-think-sft-32b-clean-aggressiveDolci-Think-SFT-7B-q35instruct
Dolci-Think-SFT-7B-q35instruct
Megatron-format tokenization of
allenai/Dolci-Think-SFT-7B
using the Qwen3.5-0.8B-Instruct tokenizer and its chat template.
Contents
156 shards, each stored as two aligned Megatron indexed datasets (one document
per conversation, one sequence per document):
train-XXXXX-of-00156.bin / .idx — token ids (int32)
train-XXXXX-of-00156_loss_mask.bin / .idx — per-token loss mask (uint8, 0/1)
624 files total (~113 GB).… See the full description on the dataset page: https://huggingface.co/datasets/yangwang92/Dolci-Think-SFT-7B-q35instruct.Dolci-Think-SFT-7B-decontaminated
Dolci-Think-SFT-7B-decontaminated
Decontaminated version of allenai/Dolci-Think-SFT-7B.
Decontamination Details
Method: 13-gram overlap detection
Original samples: 2,268,178
Cleaned samples: 2,256,891
Removed samples: 11,287 (0.50%)
Benchmarks Checked
MMLU, Ifeval, ARC, COPA, LAMBADA, OpenBookQA, Winogrande, BoolQ, HellaSwag, PIQA, Gsm8k, ALERT, GPQA, MATH, MBPP, HumanEval, SimpleQA, CommonsenseQA, DoNotAnswer, AIME24, LiveCodeBench, MATH500
dolci-think-sft-tokenized
Dolci-Think-SFT Tokenized
Pre-tokenized version of the allenai/Dolci-Think-SFT-7B dataset, ready for training with OLMo-core.
This dataset was used to train the openeurollm/OLMo-3-7B-Think-SFT checkpoints.
See also: openeurollm/dolci-instruct-sft-tokenized for the instruct (non-thinking) variant.
Dataset Details
Property
Value
Source dataset
allenai/Dolci-Think-SFT-7B
Tokenizer
allenai/Olmo-3-7B-Think-SFT
Max sequence length
32,768
Total instances
2,268… See the full description on the dataset page: https://huggingface.co/datasets/openeurollm/dolci-think-sft-tokenized.Dolci-Think-RL-7B-Completions-SFT
Dolci-Think-Completions-SFT
Dataset Summary
Dolci-Think-Completions-SFT is a set of 5,031,398 completions(!!) from the Olmo-3-7B-Think-SFT model over the prompts considered when making Dolci-Think-RL.
These completions were mainly used to filter easy data, but we believe the completions may be useful in general.
It contains 636,095 high-quality prompts covering:
Math
Code
Precise Instruction Following
General Chat
Puzzles
Each split covers one of the above domains, and… See the full description on the dataset page: https://huggingface.co/datasets/allenai/Dolci-Think-RL-7B-Completions-SFT.dolci-think-sft-32b-clean-conservativeSoofi-Think-SFT-V2-secondhalf-DEDolci-Think-SFT-7B_persona-if_Llama3_4096toksSoofi-Think-SFTSoofi-Think-SFT-V2-secondhalfSoofi-Think-SFT-V2-firsthalf-DE
Soofi-Think-SFT-V2-firsthalf-DE
German-translated version of toroe/Soofi-Think-SFT-V2-firsthalf — a large-scale supervised fine-tuning dataset featuring chain-of-thought reasoning traces (<think>...</think>) across math, science, code, and general instruction-following tasks.
The translation was produced using Qwen3-32B via vLLM, applying professional-grade translation prompts with formal German register (Sie-form for professional/technical content).
Dataset Summary… See the full description on the dataset page: https://huggingface.co/datasets/toroe/Soofi-Think-SFT-V2-firsthalf-DE.Soofi-Think-SFT-V2-firsthalf-FR
Soofi-Think-SFT-V2-firsthalf-FR
French-translated version of toroe/Soofi-Think-SFT-V2-firsthalf — a large-scale supervised fine-tuning dataset featuring chain-of-thought reasoning traces (<think>...</think>) across math, science, code, tool-calling, and general instruction-following tasks.
The translation was produced using Qwen3-32B via vLLM, applying professional-grade translation prompts targeting standard French suitable for international francophone audiences.… See the full description on the dataset page: https://huggingface.co/datasets/toroe/Soofi-Think-SFT-V2-firsthalf-FR.math-think-sft-mini
Math Think SFT Mini
Compact English mathematical-reasoning SFT data with one shortest solution per
normalized question. The train split contains 352,470 rows from
26 source lineages.
Schema
Field
Type
Meaning
id
string
Stable source-row identifier
source
string
Source lineage
question
string
Mathematical problem
steps
list[string]
Ordered nonempty reasoning steps
answer
string
Explanatory final response
Construction
Merged… See the full description on the dataset page: https://huggingface.co/datasets/cs-giung/math-think-sft-mini.