datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Infinity-Instruct
Infinity Instruct
Beijing Academy of Artificial Intelligence (BAAI)
[Paper][Code][🤗]
The quality and scale of instruction data are crucial for model performance. Recently, open-source models have increasingly relied on fine-tuning datasets comprising millions of instances, necessitating both high quality and large scale. However, the open-source community has long been constrained by the high costs associated with building such extensive and high-quality instruction… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/Infinity-Instruct.details_grimjim__Llama-3-Instruct-8B-SimPO-SPPO-Iter3-merge
Dataset Card for Evaluation run of grimjim/Llama-3-Instruct-8B-SimPO-SPPO-Iter3-merge
Dataset automatically created during the evaluation run of model grimjim/Llama-3-Instruct-8B-SimPO-SPPO-Iter3-merge.
The dataset is composed of 136 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_grimjim__Llama-3-Instruct-8B-SimPO-SPPO-Iter3-merge.full-math-private-n256-Qwen2.5-3B-Instruct-bonfull-math-private-n256-Llama-3.2-3B-Instruct-boncode_contests_instruct
Dataset Card for "code_contests_instruct"
The deepmind/code_contests dataset formatted as markdown-instruct for text generation training.
There are several different configs. Look at them. Comments:
flesch_reading_ease is computed on the description col via textstat
hq means that python2 (aka PYTHON in language column) is dropped, and keeps only rows with flesch_reading_ease 75 or greater
min-cols drops all cols except language and text
possible values for language are {'CPP'… See the full description on the dataset page: https://huggingface.co/datasets/BEE-spoke-data/code_contests_instruct.preprocessed-full-math-private-n256-Llama-3.2-3B-Instruct-boncybersecurity_32k_instruction_input_output
Dataset Card
The dataset Q&As are focused on identification of cyber threats, and text classification under the NIST taxonomy and ITC EBA IT risk classes
Dataset Details
Dataset Description
This dataset includes a mix of public reports and news and aims to be used for cyber security risk model training.
It includes 32k examples with instruction, input and output. The latter is the output from GPT.
Curated by: [Vanessa Lopes]
Language [EN]
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Vanessasml/cybersecurity_32k_instruction_input_output.details_princeton-nlp__Llama-3-8B-ProLong-512k-Instruct
Dataset Card for Evaluation run of princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
Dataset automatically created during the evaluation run of model princeton-nlp/Llama-3-8B-ProLong-512k-Instruct.
The dataset is composed of 136 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_princeton-nlp__Llama-3-8B-ProLong-512k-Instruct.full-math-private-Qwen2.5-3B-Instruct-bonpython-text-copilot-training-instruct-ai-research-2024-02-03
Python Copilot Instructions on How to Code using Alpaca and Yaml
Training and test datasets for building coding multimodal models that understand how to use the open source GitHub projects for the Agora Open Source AI Research Lab:
Agora GitHub Organization
Agora Hugging Face
This dataset is the 2024-02-03 update for the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.
Details… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-text-copilot-training-instruct-ai-research-2024-02-03.dolma_20bn_instruct_upsamplestratified-solvable-1k-math-private-Qwen2.5-3B-Instruct-bonindustrial-instruction-dataset
Industrial-Instruction Dataset
Industrial-Instruction provides benchmark and training-ready QA instances derived from industrial technical reports, designed to evaluate robustness under realistic retrieval conditions. Samples are grounded in retrieved evidence and include irrelevant retrieval, single-/multi-document support, and single-/multi-document answer settings.
Paper
Industrial-Instruction: An End-to-End Framework for Building Instruction-Tuning and… See the full description on the dataset page: https://huggingface.co/datasets/Parssky/industrial-instruction-dataset.4B-Instruct-reason-only.stride-1.k-8.statml-arxiv.qwen3-ids
4B-Instruct-reason-only.stride-1.k-8.statml-arxiv.qwen3-ids
Thoughts for next-token prediction on k=8 token chunks of JackHsieh/statML-arxiv-40M-20M, generated by
Qwen3-4B-Instruct-2507. Each thought is a few dense sentences of reasoning about the next
8 tokens after a cut, written from the document prefix alone — the generator never sees the
continuation. Stored thought_text includes the <thought>/</thought> wrapper.
This is the small-generator parity counterpart of… See the full description on the dataset page: https://huggingface.co/datasets/JackHsieh/4B-Instruct-reason-only.stride-1.k-8.statml-arxiv.qwen3-ids.full-math-private-Qwen3-4B-Instruct-2507-bonIchigo-instruction-tokenized-v0.2full-math-private-n256-Phi-4-mini-instruct-bonpython-text-copilot-training-instruct
Python Copilot Instructions on How to Code using Alpaca and Yaml
This dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.
Details
Each row contains python code, either a class method or a global function, imported modules, base classes (if any), exceptions (ordered based off the code), returns (ordered based off the code), arguments (ordered based off the… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-text-copilot-training-instruct.Qwen2.5-7B-Instruct_qwq_mix_r1_science_eval_8179
mlfoundations-dev/Qwen2.5-7B-Instruct_qwq_mix_r1_science_eval_8179
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
AIME25
HLE
LiveCodeBenchv5
HMMT
Accuracy
60.7
90.8
89.4
63.2
52.4
48.5
27.4
26.2
48.3
12.0
34.3
34.7
AIME24
Average Accuracy: 60.67% ± 2.25%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/Qwen2.5-7B-Instruct_qwq_mix_r1_science_eval_8179.details_meta-llama__Meta-Llama-3-8B-Instruct
Dataset Card for Evaluation run of meta-llama/Meta-Llama-3-8B-Instruct
Dataset automatically created during the evaluation run of model meta-llama/Meta-Llama-3-8B-Instruct.
The dataset is composed of 136 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_meta-llama__Meta-Llama-3-8B-Instruct.akabeko_instruct_v2This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "so100",
"total_episodes": 2,
"total_frames": 600,
"total_tasks": 1,
"total_videos": 4,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:2"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/akira-sasaki/akabeko_instruct_v2.Qwen2.5-7B-Instruct_qwq_mix_r1_science_eval_2870
mlfoundations-dev/Qwen2.5-7B-Instruct_qwq_mix_r1_science_eval_2870
Precomputed model outputs for evaluation.
Evaluation Results
AIME24
Average Accuracy: 60.67% ± 2.20%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1
70.00%
21
30
2
53.33%
16
30
3
53.33%
16
30
4
66.67%
20
30
5
63.33%
19
30
6
66.67%
20
30
7
60.00%
18
30
8
46.67%
14
30
9
63.33%
19
30
10
63.33%
19
30
python-text-training-instruct-ai
Python Copilot Instructions on How to Code using Alpaca and Yaml
Training and test datasets for building coding multimodal models that understand how to use the open source GitHub projects for the Agora Open Source AI Research Lab:
Agora GitHub Organization
Agora Hugging Face
This dataset is the 2024-02-03 update for the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.
Details… See the full description on the dataset page: https://huggingface.co/datasets/DevShubham/python-text-training-instruct-ai.dolma_20bn_no_instructfull-aime_2026-n256-Phi-4-mini-instruct-bonpreprocessed-full-math-private-Llama-3.2-3B-Instruct-bonQwen3-4B-Instruct-2507.rule-thoughtful-except-first.k-64.L-1024.statml-arxivMagpie-Llama-3.1-8B-Instruct-UnfilteredDataset generated using meta-llama/Llama-3.1-8B-Instruc with the MAGPIE codebase.
The filtered dataset can be found here: /HiTZ/Magpie-Llama-3.1-8B-Instruct-Filtered
System prompts used
General
<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date: December 2023\nToday Date: 26 Jul 2024\n\n<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n
Code
<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are an AI… See the full description on the dataset page: https://huggingface.co/datasets/HiTZ/Magpie-Llama-3.1-8B-Instruct-Unfiltered.Qwen2.5-1.5B-Instruct_eval_5554
mlfoundations-dev/Qwen2.5-1.5B-Instruct_eval_5554
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
MMLUPro
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
HLE
HMMT
AIME25
LiveCodeBenchv5
Accuracy
3.0
30.8
50.2
32.5
16.4
24.7
5.5
0.8
2.2
15.3
0.0
0.7
5.1
AIME24
Average Accuracy: 3.00% ± 0.88%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1
3.33%
1… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/Qwen2.5-1.5B-Instruct_eval_5554.Magpie-Llama-3.1-70B-Instruct-UnfilteredDataset generated using meta-llama/Llama-3.1-70B-Instruc with the MAGPIE codebase.
The filtered dataset can be found here: HiTZ/Magpie-Llama-3.1-70B-Instruct-Filtered
System prompts used
General
<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date: December 2023\nToday Date: 26 Jul 2024\n\n<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n
Code
<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are an AI… See the full description on the dataset page: https://huggingface.co/datasets/HiTZ/Magpie-Llama-3.1-70B-Instruct-Unfiltered.