datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
openthoughts4-code-9168-prompts-qwen3-30b-a3b-thinking-2507-n16-flattened-logprobs-k16
OpenThoughts-4 Code SDG: Qwen3-30B-A3B-Thinking-2507 (n=16, top-16 logprobs)
Synthetic generations from
Qwen/Qwen3-30B-A3B-Thinking-2507
on the Marin OpenThoughts-4 code SDG prompt
set.
Each prompt is sampled n=16 times, and for every generated token the dataset
stores the chosen-token log probability plus the top-16 log probabilities
over the vocabulary, enabling distillation, KL-style fine-tuning,
reranking, and uncertainty analysis.
Generation setup
Field… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/openthoughts4-code-9168-prompts-qwen3-30b-a3b-thinking-2507-n16-flattened-logprobs-k16.openthoughts3-en-ar-midtrain
openthoughts3-en-ar-midtrain
Arabic translation of the OpenThoughts3_1.2M split of smoltalk2 (config Mid): long mathematical reasoning traces with <think> blocks, in a two-message user/assistant format. Translated with google/gemma-4-12B-it (bf16, greedy) on A100s. All 1,135,104 source rows are present, none dropped.
The pipeline segments each message into prose and verbatim blocks (code, LaTeX, tables, and inline non-translatables are masked and never sent to the model)… See the full description on the dataset page: https://huggingface.co/datasets/SultanR/openthoughts3-en-ar-midtrain.openthoughts4-code-9168-prompts-qwen3-32b-n16-flattened-logprobs-k16
OpenThoughts-4 Code SDG: Qwen3-32B (n=16, top-16 logprobs)
Synthetic generations from
Qwen/Qwen3-32B
on the Marin OpenThoughts-4 code SDG prompt
set.
Each prompt is sampled n=16 times, and for every generated token the dataset
stores the chosen-token log probability plus the top-16 log probabilities
over the vocabulary, enabling distillation, KL-style fine-tuning,
reranking, and uncertainty analysis.
Generation setup
Field
Value
Generator model… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/openthoughts4-code-9168-prompts-qwen3-32b-n16-flattened-logprobs-k16.openthoughts4-code-9168-prompts-glm-5.2-n4
OpenThoughts-4 Code — GLM-5.2 n=4
Quality-filtered synthetic responses from
zai-org/GLM-5.2-FP8 for the
9,168 unique instruction_seed values in
mlfoundations-dev/hero_run_4_code.
Each prompt has four accepted responses, for 36,672 rows total.
Generation
Field
Value
Generator
zai-org/GLM-5.2-FP8
Samples per prompt
4
Temperature
1.0
Top-p
0.95
Maximum generated tokens
256,000
Thinking mode
enabled
Inference engine
vLLM on 8 GB200 GPUs… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/openthoughts4-code-9168-prompts-glm-5.2-n4.openthoughts4-science-26041-prompts-qwen3-30b-a3B-thinking-2507-n8-flattened-logprobs-k16
OpenThoughts-4 Science SDG: Qwen3-30B-A3B-Thinking-2507 (n=8, top-16 logprobs)
Synthetic generations from
Qwen/Qwen3-30B-A3B-Thinking-2507
on the Marin OpenThoughts-4 science SDG prompt
set.
Each prompt is sampled n=8 times, and for every generated token the dataset
stores the chosen-token log probability plus the top-16 log probabilities
over the vocabulary, enabling distillation, KL-style fine-tuning,
reranking, and uncertainty analysis.
Generation setup
Field… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/openthoughts4-science-26041-prompts-qwen3-30b-a3B-thinking-2507-n8-flattened-logprobs-k16.openthoughts4-science-26041-prompts-qwen3-32b-n8-flattened-logprobs-k16
OpenThoughts-4 Science SDG: Qwen3-32B (n=8, top-16 logprobs)
Synthetic generations from
Qwen/Qwen3-32B
on the Marin OpenThoughts-4 science SDG prompt
set.
Each prompt is sampled n=8 times, and for every generated token the dataset
stores the chosen-token log probability plus the top-16 log probabilities
over the vocabulary, enabling distillation, KL-style fine-tuning,
reranking, and uncertainty analysis.
Generation setup
Field
Value
Generator model… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/openthoughts4-science-26041-prompts-qwen3-32b-n8-flattened-logprobs-k16.openthoughts4-code-9168-prompts-qwen3-4b-n16-flattened-logprobs-k16
OpenThoughts-4 Code SDG: Qwen3-4B (n=16, top-16 logprobs)
Synthetic generations from
Qwen/Qwen3-4B
on the Marin OpenThoughts-4 code SDG prompt
set.
Each prompt is sampled n=16 times, and for every generated token the dataset
stores the chosen-token log probability plus the top-16 log probabilities
over the vocabulary, enabling distillation, KL-style fine-tuning,
reranking, and uncertainty analysis.
Generation setup
Field
Value
Generator model
Qwen/Qwen3-4B… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/openthoughts4-code-9168-prompts-qwen3-4b-n16-flattened-logprobs-k16.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.openthoughts-subsets
OpenThoughts Subsets (Forks)
This repository contains various subsets and forks of the OpenThoughts datasets.
Each configuration here is a filtered version of a larger open-source dataset, optimized for specific token limits and sources.
Dataset Structure
Each subset is available as a separate configuration. You can load a specific subset using:
from datasets import load_dataset
dataset = load_dataset("josancamon/openthoughts-subsets", "subset_name")
Subsets… See the full description on the dataset page: https://huggingface.co/datasets/josancamon/openthoughts-subsets.OpenThoughts-Agent-v1-SFT-terminus
OpenThoughts-Agent v1 SFT, normalized to the Terminus-2 contract
14,312 multi-turn terminal-agent trajectories (14,112 train / 200 holdout),
derived from open-thoughts/OpenThoughts-Agent-v1-SFT
and put through the same assistant-JSON normalizer, loss-mask contract and
length gate as NiuNiu0110/RST-SFT-Qwen3.5-27B.
The two are therefore mixable row-for-row in one SFT run.
Converter, tests, and launchers: https://github.com/k1ssloo/RST-Train
(scripts/03d_build_openthoughts_sft.py… See the full description on the dataset page: https://huggingface.co/datasets/NiuNiu0110/OpenThoughts-Agent-v1-SFT-terminus.openthoughts4-science-26041-prompts-qwen3-4b-n8-flattened-logprobs-k16
OpenThoughts-4 Science SDG: Qwen3-4B (n=8, top-16 logprobs)
Synthetic generations from
Qwen/Qwen3-4B
on the Marin OpenThoughts-4 science SDG prompt
set.
Each prompt is sampled n=8 times, and for every generated token the dataset
stores the chosen-token log probability plus the top-16 log probabilities
over the vocabulary, enabling distillation, KL-style fine-tuning,
reranking, and uncertainty analysis.
Generation setup
Field
Value
Generator model… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/openthoughts4-science-26041-prompts-qwen3-4b-n8-flattened-logprobs-k16.