datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MINT-1T-HTML
🍃 MINT-1T:Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens
🍃 MINT-1T is an open-source Multimodal INTerleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/MINT-1T-HTML.glue
Dataset Card for GLUE
Dataset Summary
GLUE, the General Language Understanding Evaluation benchmark (https://gluebenchmark.com/) is a collection of resources for training, evaluating, and analyzing natural language understanding systems.
Supported Tasks and Leaderboards
The leaderboard for the GLUE benchmark can be found at this address. It comprises the following tasks:
ax
A manually-curated evaluation dataset for fine-grained… See the full description on the dataset page: https://huggingface.co/datasets/nyu-mll/glue.dclm-baseline-1.0
DCLM-baseline
DCLM-baseline is a 4T token / 3B document pretraining dataset that achieves strong performance on language model benchmarks.
Below are comparisions of model trained on DCLM-baseline with other models in the 7B regime.
Model
Params
Tokens
Open dataset?
CORE
MMLU
EXTENDED
Open weights, closed datasets
Llama2
7B
2T
✗
49.2
45.8
34.1
DeepSeek
7B
2T
✗
50.7
48.5
35.3
Mistral-0.3
7B
?
✗
57.0
62.7
45.1
QWEN-2
7B
?
✗
57.5
71.9
50.5
Llama3
8B
15T
✗… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0.blimp
Dataset Card for "blimp"
Dataset Summary
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
Supported Tasks and Leaderboards
More Information Needed
Languages
More Information… See the full description on the dataset page: https://huggingface.co/datasets/nyu-mll/blimp.dcvlm-baseline-200b
DCVLM-Baseline (200B tokens)
DCVLM-Baseline is the reference training mixture from our DataComp-VLM paper.
It is a pre-mixed, decontaminated, ready-to-train multimodal pretraining dataset, materialized as flat
WebDataset tar shards so it can be consumed by any training
stack.
This is a 200B-token dataset release consisting of 103,985,276 samples, curated from our DCVLM-large data pool.
A smaller 6.25B-token version is also available.
⚠️ NOTE: The training data is the WebDataset… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/dcvlm-baseline-200b.dclm-baseline-1.0-parquet
DCLM-baseline
Note: this is an identical copy of https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0, where all the files have been mapped to a parquet format.
DCLM-baseline is a 4T token / 3B document pretraining dataset that achieves strong performance on language model benchmarks.
Below are comparisions of model trained on DCLM-baseline with other models in the 7B regime.
Model
Params
Tokens
Open dataset?
CORE
MMLU
EXTENDED
Open weights, closed datasets… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0-parquet.datacomp_xlarge
DataComp XLarge Pool
This repository contains metadata files for the xlarge pool of DataComp. For details on how to use the metadata, please visit our website and our github repository.
We distribute the image url-text samples and metadata under a standard Creative Common CC-BY-4.0 license. The individual images are under their own copyrights.
Terms and Conditions
We have terms of service that are similar to those adopted by HuggingFace… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/datacomp_xlarge.peoples_speech
Dataset Card for People's Speech
Dataset Summary
The People's Speech Dataset is among the world's largest English speech recognition corpus today that is licensed for academic and commercial usage under CC-BY-SA and CC-BY 4.0. It includes 30,000+ hours of transcribed speech in English languages with a diverse set of speakers. This open dataset is large enough to train speech-to-text systems and crucially is available with a permissive license.
Supported Tasks… See the full description on the dataset page: https://huggingface.co/datasets/MLCommons/peoples_speech.FineTome-100k
FineTome-100k
The FineTome dataset is a subset of arcee-ai/The-Tome (without arcee-ai/qwen2-72b-magpie-en), re-filtered using HuggingFaceFW/fineweb-edu-classifier.
It was made for my article "Fine-tune Llama 3.1 Ultra-Efficiently with Unsloth".
harmful_behaviorsharmless_alpacadcvlm-balanced-200b
DCVLM-Balanced (200B tokens)
DCVLM-Balanced is the balanced-mixture training set from our DataComp-VLM paper.
It is a pre-mixed, decontaminated, ready-to-train multimodal pretraining dataset, materialized as flat
WebDataset tar shards so it can be consumed by any training
stack.
This is a 200B-token release consisting of 112,358,849 samples, curated from our DCVLM-large data pool.
The instruction-heavy counterpart (DCVLM-baseline) is available as
dcvlm-baseline-200b, along with… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/dcvlm-balanced-200b.multi_nli
Dataset Card for Multi-Genre Natural Language Inference (MultiNLI)
Dataset Summary
The Multi-Genre Natural Language Inference (MultiNLI) corpus is a
crowd-sourced collection of 433k sentence pairs annotated with textual
entailment information. The corpus is modeled on the SNLI corpus, but differs in
that covers a range of genres of spoken and written text, and supports a
distinctive cross-genre generalization evaluation. The corpus served as the
basis for the shared task… See the full description on the dataset page: https://huggingface.co/datasets/nyu-mll/multi_nli.datacomp_1b
DataComp-1B
This repository contains metadata files for DataComp-1B. For details on how to use the metadata, please visit our website and our github repository.
We distribute the image url-text samples and metadata under a standard Creative Common CC-BY-4.0 license. The individual images are under their own copyrights.
Terms and Conditions
We have terms of service that are similar to those adopted by HuggingFace (https://huggingface.co/terms-of-service), which covers… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/datacomp_1b.MINT-1T-PDF-CC-2023-14
🍃 MINT-1T:Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens
🍃 MINT-1T is an open-source Multimodal INTerleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/MINT-1T-PDF-CC-2023-14.chempile-mlift
ChemPile-MLIFT
A comprehensive multimodal dataset for chemistry property prediction using vision large language models
📋 Dataset Summary
ChemPile-MLIFT is a dataset designed for multimodal chemistry property prediction tasks, specifically focusing on the prediction of chemical properties using vision large language models (VLLMs). It is part of the ChemPile project, which aims to create a comprehensive collection of chemistry-related data for training LLMs. The… See the full description on the dataset page: https://huggingface.co/datasets/jablonkagroup/chempile-mlift.LeMat-Bulk-MLIP-Hull
LeMat-Bulk MLIP Hull Reference Datasets
This dataset contains materials close to the convex hull computed using various ML interatomic potentials (MLIPs).
Dataset Splits
all: Contains ALL materials with hull energies for all MLIPs (no threshold filtering)
dft, orb, uma, mace_mp, mace_omat: Materials within 0.001 eV/atom of respective hulls
Energy Types
dft: DFT reference energies
orb: ORB model energies
uma: UMA model energies
mace_mp: MACE-MP model energies… See the full description on the dataset page: https://huggingface.co/datasets/LeMaterial/LeMat-Bulk-MLIP-Hull.aops_forum_filteredfrontier-ml-tasks
Frontier MLE tasks
Data for the tasks in induction-labs/frontier-ml.
Each task has one folder:
<slug>/public/ given to the coding agent verbatim, at /task/public
<slug>/private/ held-out data for the trusted verifier, at /tests/private
<slug>/artifacts/ optional starting files for the agent, at /artifacts
<slug>/manifest.json optional provenance summary
Tasks pin this repository by commit in tasks/<slug>/task.yaml. Starting model weights are
downloaded from their… See the full description on the dataset page: https://huggingface.co/datasets/inductionlabs/frontier-ml-tasks.MINT-1T-PDF-CC-2024-10
🍃 MINT-1T:Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens
🍃 MINT-1T is an open-source Multimodal INTerleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/MINT-1T-PDF-CC-2024-10.fineweb_10bt_ml_64gh-ml
GitHub ML
A continually refreshed registry of GitHub repositories across ML fields. The curated current view applies ml-contribution-v5 and seeks projects that present a distinct contribution to an ML model, method, or technique. The broader candidates view includes current-view rows and repositories with heuristic evidence of probable original ML content, as well as established qualified review cases. Candidate eligibility is independent of strict selection status: a row… See the full description on the dataset page: https://huggingface.co/datasets/modelomics/gh-ml.fineweb_10bt_ml_16MLVU_devMINT-1T-PDF-CC-2023-23
🍃 MINT-1T:Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens
🍃 MINT-1T is an open-source Multimodal INTerleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/MINT-1T-PDF-CC-2023-23.MLMRL-Library
仓库信息
电报地址：https://t.me/vomebook ，有问题请在：https://huggingface.co/datasets/VoiceOfML/MLMRL-Library/discussions 提出。
此仓库存储重要书库备份：https://huggingface.co/datasets/VoiceOfML/MLMRL-Library/tree/main 。
请使用：https://voiceofml-search.hf.space/MLMRL-Library 进行文件检索（备用搜索站：https://vomebook.github.io/search/#/MLMRL-Library ）。
可使用：https://voiceofml-search.hf.space/MLMRL-Library?wide=1 进行仓库内容查看（备用站：https://voiceofml-search.hf.space/MLMRL-Library?wide=1 ）。
你可以仅下载指针（只有文件名的信息）
If you want to clone… See the full description on the dataset page: https://huggingface.co/datasets/VoiceOfML/MLMRL-Library.MAPBench-V2For more details, please check our project page.
Paper: https://arxiv.org/abs/2601.05432
Repository: https://github.com/AMAP-ML/Thinking-with-Map
MINT-1T-ArXiv
🍃 MINT-1T:Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens
🍃 MINT-1T is an open-source Multimodal INTerleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/MINT-1T-ArXiv.mlx-model-explorer-data
MLX Model Explorer Data
An anonymous record of how people use MLX Model Explorer to choose an MLX model for their Mac: which model families, sizes, quantizations, memory classes and context lengths they look at, and which models they go on to open, compare or download. It also holds the community reports ("it worked", "too slow") and real MLX benchmark results that people choose to contribute.
The goal is to answer, with data: what is the MLX community actually trying to run… See the full description on the dataset page: https://huggingface.co/datasets/mlx-community/mlx-model-explorer-data.Eurus-2-7B-SFT_eval_2e29
mlfoundations-dev/Eurus-2-7B-SFT_eval_2e29
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
MMLUPro
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
AIME25
HLE
LiveCodeBenchv5
Accuracy
2.3
21.0
30.6
11.0
11.4
10.4
6.8
1.5
2.1
1.3
4.1
4.4
AIME24
Average Accuracy: 2.33% ± 0.67%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1
0.00%
0
30
2
3.33%
1… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/Eurus-2-7B-SFT_eval_2e29.