Snapshot 2026-10-21. Likes measure Hub popularity, not quality. Models · Methodology.
| Rank | Dataset | Likes | Size |
|---|---|---|---|
| 122 | togethercomputer/RedPajama-Data-V2 RedPajama V2: an Open Dataset for Training Large Language Models | 420 | — |
| 128 | openai/openai_humaneval The HumanEval dataset released by OpenAI includes 164 programming problems with a function sig- nature, docstring, body, and several unit tests. They were handwritten to ensure not to be included in the training set of code generation models. Supported Tasks and Leaderboards… | 410 | n<1K |
| 137 | HuggingFaceTB/finemath What is it? 📐 FineMath consists of 34B tokens (FineMath-3+) and 54B tokens (FineMath-3+ with InfiMM-WebMath-3+) of mathematical educational content filtered from CommonCrawl. To curate this dataset, we trained a mathematical content classifier using annotations generated by… | 392 | 10M<n<100M |
| 177 | mlfoundations/dclm-baseline-1.0 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… | 328 | 1B<n<10B |
| 222 | open-thoughts/OpenThoughts3-1.2M We have released a paper for OpenThoughts! See our paper here. OpenThoughts3-1.2M Open-source state-of-the-art reasoning dataset with 1.2M rows. 🚀 OpenThoughts3-1.2M is the third iteration in our line of OpenThoughts datasets, building on our previous OpenThoughts-114k and… | 277 | 1M<n<10M |
| 223 | allenai/tulu-3-sft-mixture Note that this collection is licensed under ODC-BY-1.0 license; different licenses apply to subsets of the data. Some portions of the dataset are non-commercial. We present the mixture as a research artifact. The Tulu 3 SFT mixture was used to train the Tulu 3 series of models… | 275 | 100K<n<1M |
| 254 | EssentialAI/essential-web-v1.0 🌐 Essential-Web: Complete 24-Trillion Token Dataset 🏆 Website | 🖥️ Code | 📖 Paper | ☁️ AWS 📋 Dataset Description Essential-Web is a 24-trillion-token web dataset with document-level metadata designed for flexible dataset curation. The dataset provides metadata including… | 250 | 10B<n<100B |
| 290 | nvidia/Granary Granary: Speech Recognition and Translation Dataset in 25 European Languages Granary is a large-scale, open-source multilingual speech dataset covering 25 European languages for Automatic Speech Recognition (ASR) and Automatic Speech Translation (AST) tasks. Overview Granary… | 231 | 100M<n<1B |
| 380 | SWE-bench/SWE-bench_Verified SWE-bench Verified is a subset of 500 samples from the SWE-bench test set, which have been human-validated for quality. SWE-bench is a dataset that tests systems’ ability to solve GitHub issues automatically. See this post for more details on the human-validation process. The… | 189 | n<1K |
| 409 | HuggingFaceTB/smoltalk2 This dataset contains three subsets (Mid, SFT, Preference) that correspond to the three phases of Post-Training for SmolLM3-3B. You can find more details in our blog post about how we used the data in each of the stages SmolLM3. The specific weight of each subset is available… | 181 | 1M<n<10M |
| 446 | arcinstitute/opengenome2 OpenGenome2 is a database of nearly 9 trillion base pairs of curated DNA from across all domains of life. Collected from diverse species and public data sources, OpenGenome2 was used to train Evo 2 models. Please refer to the Evo 2 preprint or github repository for further… | 168 | n>1T |
| 501 | princeton-nlp/SWE-bench SWE-bench is a dataset that tests systems’ ability to solve GitHub issues automatically. The dataset collects 2,294 Issue-Pull Request pairs from 12 popular Python repositories. Evaluation is performed by unit test verification using post-PR behavior as the reference solution… | 153 | 10K<n<100K |
| 507 | nvidia/Nemotron-CC-v2 This pretraining dataset, for generative AI model training, preserves high-value math and code while enriching it with diverse multilingual Q&A, fueling the next generation of intelligent, globally-capable models. This dataset supports NVIDIA Nemotron Nano 2, a family of large… | 150 | 1B<n<10B |
| 527 | nvidia/Nemotron-CC-v2.1 The Nemotron-Pre-Training-Dataset-v2.1 extends the previously released Nemotron pretraining datasets with refreshed, higher-quality, and more diverse data across math, code, English Common Crawl, and large-scale synthetic corpora. Designed for the NVIDIA Nemotron 3 family of… | 144 | 1B<n<10B |
| 560 | gorilla-llm/Berkeley-Function-Calling-Leaderboard The Berkeley function calling leaderboard is a live leaderboard to evaluate the ability of different LLMs to call functions (also referred to as tools). We built this dataset from our learnings to be representative of most users' function calling use-cases, for example, in… | 136 | — |
| 634 | EleutherAI/the_pile_deduplicated | 122 | 100M<n<1B |
| 803 | bigcode/bigcodebench BigCodeBench-Complete: Code Completion based on the structured docstrings. BigCodeBench-Instruct: Code Generation based on the NL-oriented instructions. The overall statistics of the dataset are as follows: Complete Instruct # Task 1140 1140 # Avg. Test Cases 5.6 5.6 #… | 94 | 1K<n<10K |
| 804 | HuggingFaceTB/stack-edu Stack-Edu is a 125B token dataset of educational code filtered from The Stack v2, precisely the curated training corpus of StarCoder2 models denoted StarCoder2Data. It is intended for Language Models training. This dataset was curated using a classifier-based filtering… | 84 | 100M<n<1B |
| 805 | Zyphra/Zyda Zyda is a 1.3T language modeling dataset created by collecting open and high quality datasets and combining them and performing a uniform filtering and deduplication step. We find that Zyda performs extremely well in ablations and is at least comparable and potentially better… | 84 | 1B<n<10B |
| 807 | nvidia/Nemotron-Pretraining-Dataset-sample This pretraining dataset, for generative AI model training, preserves high-value math and code while enriching it with diverse multilingual Q&A, fueling the next generation of intelligent, globally-capable models. This dataset supports NVIDIA Nemotron Nano 2, a family of large… | 70 | 10K<n<100K |
| 808 | allenai/Dolci-Instruct-SFT Note that this collection licensed under ODC-BY. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines. The Dolci Instruct SFT mixture was used to train Olmo 3 7B Instruct SFT. It contains 2,152,112 samples from the following sets… | 63 | 1M<n<10M |
| 809 | allenai/dolma3_mix-6T-1025-7B ⚠️ WARNING: This dataset is intended ONLY for reproducing Olmo 3 7B ⚠️ For all other training use cases, including training from scratch, please utilize our primary dolma 3 data mix: Note: Some olmOCR science PDFs in the current dataset have been redacted following the training… | 56 | 1B<n<10B |
| 810 | allenai/dolma3_pool This is the Dolma 3 pool, pre–quality upsampling and mixing. If you are interested in the data used to train Olmo 3 7B and Olmo 3 32B, visit allenai/dolma3_mix-6T-1025. Dolma 3 Pool The Dolma 3 pool is a dataset of over 9 trillion tokens from a diverse mix of web content… | 42 | 10B<n<100B |
| 811 | allenai/dolma3_mix-6T The Dolma 3 Mix (6T) is the collection of data used during the pretraining stage to train the Olmo-3-1125-32B model. This dataset is made up of ~6 trillion tokens from a diverse mix of web content, academic publications, code, and more. The majority of this dataset comes from… | 39 | — |
| 812 | allenai/Dolci-Think-SFT-32B 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… | 32 | 1M<n<10M |
| 813 | allenai/dolma3_dolmino_mix-100B-1125 Dolma 3 Dolmino dataset pool for Olmo 3 stage 2 annealing training This dataset contains the high-quality pool of data considered for the second stage of Olmo 3 32B. Dataset Sources Source Category TinyMATH Mind Math (synth) TinyMATH PoT Math (synth) CraneMath Math (synth)… | 28 | — |
| 814 | meta-llama/Llama-3.1-8B-evals This dataset contains the Meta evaluation result details for Llama-3.1-8B. The dataset has been created from 12 evaluation tasks. These tasks are triviaqa__wiki, mmlu_pro, commonsenseqa, winogrande, mmlu, boolq, squad, quac, drop, bbh, arc_challenge, agieval_english. Each task… | 28 | 10K<n<100K |
| 815 | allenai/Dolci-Think-RL-32B Dolci-Think-RL is a deliberate reasoning RL dataset used for training Olmo-3-32B-Think model. It contains 102,026 high-quality prompts covering: Math Code Precise Instruction Following General Chat This dataset is structurally similar to Dolci-Think-RL-7B but with slightly… | 27 | 100K<n<1M |
| 816 | allenai/dolma3_longmino_mix-100B-1125 The Dolma 3 Longmino Mix (100B) is the mixture of data used for the third stage of training for Olmo 3 32B model. Dataset Sources Source Type LC-s2pdf-REX 32k-64k Synth PDFs LC-s2pdf-CWE 32k-64k Synth PDFs LC-s2pdf 32k-64k PDFs LC-s2pdf 8k-32k (8-16k) PDFs LC-s2pdf 8k-32k… | 19 | — |
| 817 | mit-han-lab/awq-model-zoo | 19 | — |
| 818 | allenai/Dolci-Instruct-DPO This dataset is licensed under ODC-BY. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines. The Dolci Instruct DPO mixture was used to preference tune Olmo 3 Instruct 7B. It contains 260,000 preference pairs in total, including… | 17 | 100K<n<1M |
| 819 | futurehouse/ether0-benchmark QA benchmark (test set) for the ether0 reasoning language model: This benchmark is made from commonly used tasks - like reaction prediction in USPTO/ORD, molecular captioning from PubChem, or predicting GHS classification. It's unique from other benchmarks in that all answers… | 17 | n<1K |
| 820 | allenai/Dolci-Instruct-RL Dolci-Instruct-RL is the reinforcement learning dataset used to train the Olmo-3-7B-Instruct model.It contains 169,964 prompts spanning: Math Code Precise Instruction Following General Chat The dataset aggregates multiple curated sources, applies extensive filtering, and… | 15 | 100K<n<1M |
| 821 | allenai/Molmo2-Cap Molmo2-Cap is a dataset of very long (average 900 words), detailed video captions. It can be used to pre-train and fine-tune vision-language models. Molmo2-Cap is part of the Molmo2 dataset collection and was used to train the Molmo2 family of models. Quick links: 📃 Paper 🎥… | 15 | 100K<n<1M |
| 822 | microsoft/bleeding-edge-gameplay-sample This dataset contains 1024 60 second video clips of Bleeding Edge gameplay (75GB). The data has already been processed into the following format: 300x180 videos sampled at 10 fps. Dataset Structure Data Files testing_dataset_part1.zip & testing_dataset_part2.zip – Contains all… | 12 | — |
| 823 | allenai/Dolci-Think-DPO-32B This dataset is licensed under ODC-BY. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines. The Dolci Think DPO mixture was used to preference tune Olmo 3 Think 32B. It contains 200,000 preference pairs created with the preference… | 11 | 100K<n<1M |
| 824 | allenai/dolma3_dolmino_mix-100B-1025 The Dolma 3 Dolmino Mix (100B) is the mixture of high-quality data used for the second stage of training for Olmo 3 7B model. Dataset Sources Source Category Tokens Documents TinyMATH Mind Math (synth) 898M (0.9%) 1.52M TinyMATH PoT Math (synth) 241M (0.24%) 758K CraneMath Math… | 11 | 10M<n<100M |
| 825 | allenai/dolma3_longmino_mix-50B-1025 The Dolma 3 Longmino Mix (50B) is the mixture of data used for the third stage of training for Olmo 3 7B model. Dataset Sources Source Type Tokens Docs LC-s2pdf-REX 32k-64k Synth PDFs 6.08B (12.2%) 217K LC-s2pdf-CWE 32k-64k Synth PDFs 1.94B (3.88%) 71.3K LC-s2pdf 32k-64k PDFs… | 11 | — |
| 826 | cais/hle-diamond IMPORTANT: Please help us protect the integrity of this benchmark by not publicly sharing, re-uploading, or distributing the dataset. Humanity's Last Exam: Diamond 🌐 Website | 📄 Paper | GitHub Center for AI Safety & Scale AI We are releasing HLE-Diamond, a refined subset of… | 11 | 1K<n<10K |
| 827 | allenai/dolma3.5_pool This is the Dolma 3.5 pool. It contains no quality upsampling or mixing. This is an updated version of the Dolma 3 pool with additional quality filtering and more data sources. If you are interested in the data used to train Olmo 3 7B and Olmo 3 32B, visit… | 9 | — |
| 829 | EleutherAI/pile-standard-pythia-preshuffled | 5 | — |
| 830 | NousResearch/eval-Hermes-4-70B-reasoning hermes-4-70b-reasoning-40k Evaluation Results Summary Benchmark Score Metric Samples Overlong rate aime24 0.735 math_pass@1:64_samples 64 8.4% aime25 0.674 math_pass@1:64_samples 64 9.6% arenahard 0.901 eval/overall_winrate 500 0.0% bbh_generative 0.878 extractive_match 1 4.8%… | 5 | 100K<n<1M |
| 831 | NousResearch/eval-Hermes-4.3-36B 0.1%… | 5 | 100K<n<1M |
| 835 | EssentialAI/rnj-1-instruct-evals | 1 | 10K<n<100K |
| 836 | EleutherAI/pile_val_test The Pile: Validation and Test Splits This repo contains the validation and test splits of The Pile, an 825 GiB English text dataset designed for training large language models. Files File Split Size val.jsonl Validation 1.4 GB test.jsonl Test 1.3 GB Format Each line is a JSON… | 0 | 100K<n<1M |