{"data":{"slug":"ahammadmejbah-awesome-datasets-hub","name":"Awesome-Datasets-Hub","tagline":"Curated collection of datasets for Large Language Models (LLMs)","github_url":"https://github.com/ahammadmejbah/Awesome-Datasets-Hub","owner":"ahammadmejbah","repo":"Awesome-Datasets-Hub","owner_avatar_url":"https://avatars.githubusercontent.com/u/56669333?v=4","primary_language":null,"stars":148,"forks":40,"topics":["benchmark","benchmarking","deep-learning","deep-neural-networks","deeplearning","genetic-algorithm","llm","llm-evaluation","llm-inference","machine-learning","machine-learning-algorithms","machinelearning","neural-network"],"archived":false,"github_pushed_at":"2026-06-20T07:06:51+00:00","maintenance_label":"Slowing","stars_delta_30d":2,"url":"https://www.graphcanon.com/tools/ahammadmejbah-awesome-datasets-hub","markdown_url":"https://www.graphcanon.com/tools/ahammadmejbah-awesome-datasets-hub.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/ahammadmejbah-awesome-datasets-hub","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=ahammadmejbah-awesome-datasets-hub","description":"A curated collection of datasets for Large Language Models (LLMs), covering medical AI, NLP, multimodal learning, instruction tuning, reasoning, code generation, and evaluation benchmarks.","homepage_url":"https://intelligenceacademy.ai/datasets","license":null,"open_issues":1,"watchers":1,"ai_summary":"A repository featuring a variety of datasets essential for training and evaluating large language models in domains such as medical AI, NLP, multimodal learning, instruction tuning, reasoning, code generation, and evaluation benchmarks.","readme_excerpt":"\"Description\"\n\n

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\n\n## ⚡ Medical Datasets for LLM\n| Serial | Dataset | Domain | Field / Task | Scale | Strength | Language | License |\n|---|---|---|---|---|---|---|---|\n| **01** | [**MedQA (USMLE)**](https://github.com/jind11/MedQA)
Jin et al. · 2021 | | Medical QA · Licensing Exam | **12,723 Q** | | | |\n| **02** | [**MedMCQA**](https://medmcqa.github.io)
Pal et al. · 2022 | | Medical MCQ · Indian Licensing | **194K Q** | | | |\n| **03** | [**PubMedQA**](https://pubmedqa.github.io)
Jin et al. · 2019 | | Biomedical QA · Yes/No/Maybe | **273K QA** | | | |\n| **04** | [**BioASQ**](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1703-7)
Tsatsaronis et al. | | Biomedical QA · Semantic Indexing | **5,600+ Q** | | | |\n| **05** | [**MASH-QA**](https://github.com/mingzhu0527/MASHQA) | | Healthcare QA · Multi-span | **35K QA** | | | |\n| **06** | [**MedQuAD**](https://github.com/abachaa/MedQuAD) | | Consumer Medical QA | **47K QA** | | | |\n| **07** | [**LiveQA Medical**](https://github.com/abachaa/LiveQA_MedicalTask_TREC2017) | | Consumer Health QA | **634 Q** | | | |\n| **08** | [**MedS-Bench**](https://henrychur.github.io/MedS-Bench/) | | Clinical Evaluation | **13 tasks** | | | |\n| **09** | [**COVID-QA**](https://huggingface.co/datasets/deepset/covid_qa_deepset) | | COVID-19 Reading QA | **2,019 QA** | | | |\n| **10** | [**MIMIC-III**](https://physionet.org/content/mimiciii/) | | ICU EHR + Clinical Notes | **46K patients** | | | |\n| **11** | [**MIMIC-IV**](https://physionet.org/content/mimiciv/) | | Hospital EHR Records | **299K patients** | | | |\n| **12** | [**n2c2 / i2b2 Challenges**](https://n2c2.dbmi.hms.harvard.edu) | | Clinical NLP Challenges | **Multi-year** | | | |\n| **13** | [**MedNLI**](https://physionet.org/content/mednli/) | | Clinical Textual Entailment | **14K pairs** | | | |\n| **14** | [**emrQA**](https://huggingface.co/datasets/bigbio/emrqa) | | Clinical QA over EHR | **1M+ QA** | | | |\n| **15** | [**MTSamples**](https://mtsamples.com) | | Clinical Transcription Notes | **5K+ reports** | | | |\n| **16** | [**EHRNoteQA**](https://physionet.org/content/ehrnoteqa/)
PhysioNet · 2023 | | Clinical Note Question Answering | **2.4K QA** | | | |\n| **17** | [**Asclepius**](https://huggingface.co/datasets/starmpcc/Asclepius-Synthetic-Clinical-Notes)
STAR-MPCC · 2023 | | Synthetic Clinical Notes | **158K Notes** | | | |\n| **18** | [**GatorTron Corpus**](https://arx","github_created_at":"2026-05-15T14:58:14+00:00","created_at":"2026-07-11T12:02:19.399398+00:00","updated_at":"2026-09-20T07:00:50.797236+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"}],"tags":[{"slug":"benchmark","name":"benchmark"},{"slug":"code-generation","name":"code-generation"},{"slug":"instruction-tuning","name":"instruction-tuning"},{"slug":"llm-evaluation","name":"llm-evaluation"},{"slug":"medical-ai","name":"medical-ai"},{"slug":"multimodal-learning","name":"multimodal-learning"},{"slug":"nlp","name":"nlp"},{"slug":"reasoning","name":"reasoning"}],"trust":{"provenance":{"is_fork":false,"github_id":1239898419,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T07:00:47.985Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":91,"last_release_at":null,"stars_delta_30d":2,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T12:02:21.507Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T07:00:49.971Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["You need comprehensive datasets for clinical evaluation or specialized biomedical QA tasks.","Specific domain expertise is required in medical AI or health-related LLM instruction tuning."],"when_not_to_use":["Your focus is on domains outside of healthcare and medicine, where this tool might not provide adequate data diversity.","You seek real-time dataset updates, as the specific update cadence for Awesome-Datasets-Hub isn't publicly specified."],"source":"enrich:decision_facts","observed_at":"2026-07-12T18:13:48.519Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Awesome-Datasets-Hub offers a curated selection of datasets focusing particularly on medical AI, NLP, and multimodal applications, essential for training large language models."}]}}