datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MiniMax-M2.1-Mixture-of-Thoughts
MiniMax-M2.1 Mixture of Thoughts
This dataset contains responses generated by MiniMax-M2.1 for user questions from the open-r1/Mixture-of-Thoughts dataset.
Dataset Description
The dataset captures both the extended thinking process and final answers from MiniMax-M2.1, with reasoning wrapped in <think> tags for easy separation.
Metric
Value
Examples
349,317
Total Tokens
4,052,592,552
Avg Tokens/Example
11,601
Source Dataset
Name:… See the full description on the dataset page: https://huggingface.co/datasets/PursuitOfDataScience/MiniMax-M2.1-Mixture-of-Thoughts.open-thoughts-4-math-qwen3-32b-annotated
Dataset Card for Open-Thoughts-4-Math-Qwen3-32B-Annotated
This dataset is the Qwen3-32B annotated version of mlfoundations-dev/hero_run_4_math curated by the
OpenThoughts4 team. We provide the responses from Qwen3-32B in the generated_text column. These samples were generated using temperature = 0.8 and max output tokens = 7,500.
We note that many of the responses are truncated, so use this dataset wisely!
Dataset Details
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-math-qwen3-32b-annotated.open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8
Open Thoughts 4 - Math (Qwen3-32B, 32K tokens, n=8)
This dataset contains math reasoning problems with 8 independent responses generated by Qwen3-32B.
Overview
Source: marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens
Model: Qwen/Qwen3-32B
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The math problem prompt
_source
Source dataset identifier
gpt41_mini_response
Reference response from… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8.open-thoughts-4-30k-code-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8
Open Thoughts 4 - Code (Qwen3-30B-A3B-Thinking-2507, 32K tokens, n=8)
This dataset contains code reasoning problems with 8 independent responses generated by Qwen3-30B-A3B-Thinking-2507.
Overview
Source: marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated (prompts only)
Model: Qwen/Qwen3-30B-A3B-Thinking-2507
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The code problem prompt
_source
Source dataset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-code-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8.open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8
Open Thoughts 4 - Math (Qwen3-30B-A3B-Thinking-2507, 32K tokens, n=8)
This dataset contains math reasoning problems with 8 independent responses generated by Qwen3-30B-A3B-Thinking-2507.
Overview
Source: marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated (base prompts)
Model: Qwen/Qwen3-30B-A3B-Thinking-2507
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The math problem prompt
_source
Source dataset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8.open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8-reformatted
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-30B-A3B-Thinking-2507-Annotated-32768-Tokens-N8-Reformatted
Overview
This dataset is a reformatted version of marin-community/open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8. The original dataset contained 29,963 samples, each with 8 responses generated by the same model with different random seeds (stored in generated_text, generated_text2, ..., generated_text8 columns). This reformatted… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8-reformatted.open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8
Open Thoughts 4 - Math (Qwen3-4B, 32K tokens, n=8)
This dataset contains math reasoning problems with 8 independent responses generated by Qwen3-4B.
Overview
Source: marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens (n=1 version with 1 response per prompt)
Model: Qwen/Qwen3-4B
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The math problem prompt
_source
Source dataset identifier… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8.r1-thoughtsMerges open-thoughts/OpenThoughts-114k, cognitivecomputations/dolphin-r1, bespokelabs/Bespoke-Stratos-17k
and includes the question and response length in Qwen 2.5 tokens.
import datasets
import transformers
def ot_map_format(example):
conversation = example['conversations']
assert type(conversation) == list
assert len(conversation) == 2
problem = conversation[0]['value'].strip()
solution = conversation[1]['value'].strip()
solution =… See the full description on the dataset page: https://huggingface.co/datasets/ricdomolm/r1-thoughts.open-thoughts-4-6865-math-kimi-k2pt5-annotated-32768-tokens-n8-reformatted
open-thoughts-4-6865-math-kimi-k2pt5-annotated-32768-tokens
Math reasoning responses generated by Kimi K2.5 (moonshotai/Kimi-K2.5) via a Together AI dedicated instance.
Overview
Total rows: 54,920
Unique prompts: 6,865 (each with 8 response annotations)
Source prompts: marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8-reformatted
Generation model: moonshotai/Kimi-K2.5
Max tokens: 32,768
Temperature: 0.8
Tokenizer used for stats: Qwen/Qwen2.5-3B… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-6865-math-kimi-k2pt5-annotated-32768-tokens-n8-reformatted.open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-4B-Annotated-32768-Tokens
Overview
This dataset is a variant of the OpenThoughts-4 30K math subset with responses generated by Qwen/Qwen3-4B using max output tokens = 32768, allowing for longer and more complete chain-of-thought reasoning.
Generation Details
Model: Qwen/Qwen3-4B
Temperature: 0.8
Max Output Tokens: 32768
Dataset Statistics
Number of Samples: 29,963
Split: train
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens.open-thoughts-4-30k-code-qwen3-32b-annotated-32768-tokens
Dataset Card for Open-Thoughts-4-30K-Code-Qwen3-32B-Annotated-32768-Tokens
Overview
This dataset is a variant of marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated with an extended maximum sequence length. The responses in the generated_text column were generated with max output tokens = 32768 (instead of 7500 in the original dataset), allowing for longer and more complete chain-of-thought reasoning.
Generation Details
Model: Qwen/Qwen3-32B… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated-32768-tokens.open-thoughts-4-science-qwen3-32b-annotated
Dataset Card for Open-Thoughts-4-Science-Qwen3-32B-Annotated
This dataset is the Qwen3-32B annotated version of mlfoundations-dev/hero_run_4_science curated by the
OpenThoughts4 team. We provide the responses from Qwen3-32B in the generated_text column. These samples were generated using temperature = 0.8 and max output tokens = 7,500.
We note that many of the responses are truncated, so use this dataset wisely!
Dataset Details
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-science-qwen3-32b-annotated.open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8-reformatted-selfconsistency
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-32B-Annotated-32768-Tokens-N8-Reformatted-SelfConsistency
Overview
This dataset is a self-consistency filtered version of marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8-reformatted. For each prompt, 8 responses were generated by Qwen3-32B with different random seeds. A majority vote was taken over the final answers (extracted from \boxed{...}) to determine the most popular answer, and only… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8-reformatted-selfconsistency.open-thoughts-4-30k-math-qwen3-32b-annotated
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-32B-Annotated
This dataset is a 29,963 sample subset of marin-community/open-thoughts-4-math-qwen3-32b-annotated, originally derived from mlfoundations-dev/hero_run_4_math curated by the OpenThoughts4 team.
We provide the responses from Qwen/Qwen3-32B in the generated_text column. These samples were generated using temperature = 0.8 and max output tokens = 7500. Note that many of the responses are truncated.
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated.open-thoughts-4-30k-math-qwen3-235b-a22b-annotated-32768-tokens
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-235B-A22B-Annotated-32768-Tokens
Overview
This dataset is a variant of marin-community/open-thoughts-4-30k-math-qwen3-235b-a22b-annotated with an extended maximum sequence length. The responses in the qwen235b_generated_text column were regenerated with max output tokens = 32768 (instead of 16000 in the original dataset), allowing for longer and more complete chain-of-thought reasoning. The conversations column has been… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-235b-a22b-annotated-32768-tokens.rlvr_mixin_it_up_prompts-qwen3-32b-06B-thoughts-x8-filtered-no-chineseopen-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-rejection-sampling-soft-match
N8 Rejection Sampling (Soft Match)
Overview
This dataset was created via rejection sampling from the Qwen3-4B response dataset using Qwen3-32B answers as ground truth.
Source dataset (Qwen3-4B, 8 responses per prompt): marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-reformatted
Verifier dataset (Qwen3-32B, 1 response per prompt): marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens
Creator: The Marin Project
How… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-rejection-sampling-soft-match.aprm-sft-thoughts-tau2-retail-policy_best-adamw30-lp0
Act-PRM SFT thoughts — tau2-bench retail
Act-PRM (Action Process Reward Models) infers the latent thoughts behind
logged, action-only agent demonstrations via an offline EM. For each
logged action x in state s we sample G=4 candidate thoughts z,
score each by the length-penalized action likelihood
reward(z) = p(x | s, z)
(len_frac grows with the thought's token length), and mark the best thought
(argmax reward). The (thought + action) span is then what downstream SFT / RL… See the full description on the dataset page: https://huggingface.co/datasets/mzio/aprm-sft-thoughts-tau2-retail-policy_best-adamw30-lp0.NR-short-32k-16-thoughts-4k-8-thoughtsSubsample of JackHsieh/NR-short-32k-16-thoughts-4k-128-thoughts, with a smaller test set.
open-thoughts-4-30k-math-qwen3-32b-annotated-16384-tokens
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-32B-Annotated-16384-Tokens
This dataset is a variant of marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated with an extended maximum sequence length. The responses in the generated_text column were generated with max output tokens = 16384 (instead of 7500 in the original dataset), allowing for longer and more complete chain-of-thought reasoning.
We provide the responses from Qwen/Qwen3-32B in the generated_text column. These… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-16384-tokens.open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-rejection-sampling-strict-match
N8 Rejection Sampling (Strict Match)
Overview
This dataset was created via rejection sampling from the Qwen3-4B response dataset using Qwen3-32B answers as ground truth.
Source dataset (Qwen3-4B, 8 responses per prompt): marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-reformatted
Verifier dataset (Qwen3-32B, 1 response per prompt): marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens
Creator: The Marin Project… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-rejection-sampling-strict-match.aprm-sft-thoughts-tau2-airline-policy_best-adamw30-lp0
Act-PRM SFT thoughts — tau2-bench airline
Act-PRM (Action Process Reward Models) infers the latent thoughts behind
logged, action-only agent demonstrations via an offline EM. For each
logged action x in state s we sample G=4 candidate thoughts z,
score each by the length-penalized action likelihood
reward(z) = p(x | s, z)
(len_frac grows with the thought's token length), and mark the best thought
(argmax reward). The (thought + action) span is then what downstream SFT / RL… See the full description on the dataset page: https://huggingface.co/datasets/mzio/aprm-sft-thoughts-tau2-airline-policy_best-adamw30-lp0.aprm-sft-thoughts-snorkel-insurance-policy_best-adamw30-lp0
Act-PRM SFT thoughts — snorkel-insurance insurance
Act-PRM (Action Process Reward Models) infers the latent thoughts behind
logged, action-only agent demonstrations via an offline EM. For each
logged action x in state s we sample G=4 candidate thoughts z,
score each by the length-penalized action likelihood
reward(z) = p(x | s, z)
(len_frac grows with the thought's token length), and mark the best thought
(argmax reward). The (thought + action) span is then what downstream SFT… See the full description on the dataset page: https://huggingface.co/datasets/mzio/aprm-sft-thoughts-snorkel-insurance-policy_best-adamw30-lp0.open-thoughts-4-30k-code-qwen3-32b-annotated
Dataset Card for Open-Thoughts-4-30K-Code-Qwen3-32B-Annotated
This dataset is a 29,963 sample subset of marin-community/open-thoughts-4-code-qwen3-32b-annotated, originally derived from mlfoundations-dev/hero_run_4_code curated by the OpenThoughts4 team.
We provide the responses from Qwen/Qwen3-32B in the generated_text column. These samples were generated using temperature = 0.8 and max output tokens = 7500.Note that many of the… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated.open-thoughts-4-30k-math-qwen3-235b-a22b-annotated
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-235B-A22B-Annotated
This dataset is the Qwen3-235B-A22B annotated version of a 29,963 sample subset from marin-community/open-thoughts-4-math-qwen3-32b-annotated, originally derived from mlfoundations-dev/hero_run_4_math curated by the OpenThoughts4 team.
We provide the responses from Qwen/Qwen3-235B-A22B-FP8 in the qwen235b_generated_text column. These samples were generated using temperature = 0.8 and max output tokens = 16000. Note… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-235b-a22b-annotated.open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-32B-Annotated-32768-Tokens
Overview
This dataset is a variant of marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated with an extended maximum sequence length. The responses in the generated_text column were generated with max output tokens = 32768 (instead of 7500 in the original dataset), allowing for longer and more complete chain-of-thought reasoning.
Generation Details
Model: Qwen/Qwen3-32B… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens.open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n1-rejection-sampling-quantity-match
N1 Rejection Sampling (Quantity Match)
Overview
This dataset was created via rejection sampling from the Qwen3-4B response dataset using Qwen3-32B answers as ground truth.
Source dataset (Qwen3-4B, 8 responses per prompt): marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8-reformatted
Verifier dataset (Qwen3-32B, 1 response per prompt): marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens
Creator: The Marin Project… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n1-rejection-sampling-quantity-match.open-thoughts-4-30k-code-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8-reformatted
Dataset Card for Open-Thoughts-4-30K-Code-Qwen3-30B-A3B-Thinking-2507-Annotated-32768-Tokens-N8-Reformatted
Overview
This dataset is a reformatted version of marin-community/open-thoughts-4-30k-code-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8. The original dataset contained 29,963 samples, each with 8 responses generated by the same model with different random seeds (stored in generated_text, generated_text2, ..., generated_text8 columns). This reformatted… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-code-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8-reformatted.aprm-sft-thoughts-snorkel-finance-policy_best-adamw30-lp0
Act-PRM SFT thoughts — snorkel-finance finance
Act-PRM (Action Process Reward Models) infers the latent thoughts behind
logged, action-only agent demonstrations via an offline EM. For each
logged action x in state s we sample G=4 candidate thoughts z,
score each by the length-penalized action likelihood
reward(z) = p(x | s, z)
(len_frac grows with the thought's token length), and mark the best thought
(argmax reward). The (thought + action) span is then what downstream SFT / RL… See the full description on the dataset page: https://huggingface.co/datasets/mzio/aprm-sft-thoughts-snorkel-finance-policy_best-adamw30-lp0.NR-short-32k-16-thoughts-4k-8-thoughts-Qwen3-1.7B