datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
damru-knowledge
🐕 Damru Knowledge
A continuously growing, self-collected question-answer knowledge base that powers Damru AI — a self-learning assistant built for exam preparation and general-purpose help, with a focus on Indian students.
The dataset is harvested and quality-filtered automatically, 24x7, from multiple open sources and a self-evaluating reasoning engine. New rows are appended every hour as parquet shards under data/.
📦 What's inside
Column
Type
Description… See the full description on the dataset page: https://huggingface.co/datasets/Damaru-ai/damru-knowledge.python-image-copilot-training-using-import-knowledge-graphs
Python Copilot Image Training using Import Knowledge Graphs
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 a png file in the dbytes column.
Rows: 216642
Size: 211.2 GB
Data type: png
Format: Knowledge graph using NetworkX with alpaca text box
Schema
The png is in the dbytes column:
{
"dbytes": "binary"… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-image-copilot-training-using-import-knowledge-graphs.python-image-copilot-training-using-class-knowledge-graphs
Python Copilot Image Training using Class Knowledge Graphs
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 a png file in the dbytes column.
Rows: 312277
Size: 304.3 GB
Data type: png
Format: Knowledge graph using NetworkX with alpaca text box
Schema
The png is in the dbytes column:
{
"dbytes": "binary"… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-image-copilot-training-using-class-knowledge-graphs.General-Knowledge
Dataset Card for Dataset Name
Dataset Summary
The dataset is a collection of questions and answers themed on general facts and reasoning. The dataset is divided into two features - 'Question' and 'Answer'.
It is meant to be used for training a model to be good at general knowledge and reasoning. This dataset is inspired from the Alpaca dataset, and infact contains a subset of the alpaca dataset in itself.
Distribution
The distribution of the… See the full description on the dataset page: https://huggingface.co/datasets/MuskumPillerum/General-Knowledge.python-audio-copilot-training-using-class-knowledge-graphs
Python Copilot Audio Training using Class with Knowledge Graphs
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 class method has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet dbytes column and the associated source code file_path identifier.
Rows:… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-audio-copilot-training-using-class-knowledge-graphs.python-audio-copilot-training-using-function-knowledge-graphs
Python Copilot Audio Training using Global Functions with Knowledge Graphs
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 global function has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet dbytes column and the associated source code file_path… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-audio-copilot-training-using-function-knowledge-graphs.python-audio-copilot-training-using-import-knowledge-graphs
Python Copilot Audio Training using Imports with Knowledge Graphs
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 imported module for each unique class in each module file has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet dbytes column and the… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-audio-copilot-training-using-import-knowledge-graphs.python-audio-copilot-training-using-inheritance-knowledge-graphs
Python Copilot Audio Training using Inheritance and Polymorphism Knowledge Graphs
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 base class for each unique class in each module file has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet dbytes column and… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-audio-copilot-training-using-inheritance-knowledge-graphs.python-audio-copilot-training-using-class-knowledge-graphs-2024-01-27
Python Copilot Audio Training using Class with Knowledge Graphs
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 class method has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet dbytes column and the associated source code file_path identifier.
Rows:… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-audio-copilot-training-using-class-knowledge-graphs-2024-01-27.python-image-copilot-training-using-inheritance-knowledge-graphs
Python Copilot Image Training using Inheritance and Polymorphism Knowledge Graphs
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 a png file in the dbytes column.
Rows: 259017
Size: 135.2 GB
Data type: png
Format: Knowledge graph using NetworkX with alpaca text box
Schema
The png is in the dbytes column:
{… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-image-copilot-training-using-inheritance-knowledge-graphs.med_knowledge_prob
Adapting LLMs to Domains via Continual Pre-Training (ICLR 2024)
This repo contains the Biomedicine Knowledge Probing dataset used in our paper Adapting Large Language Models via Reading Comprehension.
We explore continued pre-training on domain-specific corpora for large language models. While this approach enriches LLMs with domain knowledge, it significantly hurts their prompting ability for question answering. Inspired by human learning via reading comprehension, we propose a… See the full description on the dataset page: https://huggingface.co/datasets/AdaptLLM/med_knowledge_prob.cancer-knowledge-base
Cancer Knowledge Base — the open, verified oncology KB for RAG & LLM evaluation
The only open CC-BY-4.0 oncology knowledge base that combines:
110/110 trials cited with PMID + NCT + PubMed/ClinicalTrials.gov URLs, and 32 prognosis
rows linked to verified SEER 2016–2022 references — no LLM-synthetic dataset has this.
A provable 152-question MCQ benchmark — every answer derives from this KB's own structured
data and carries a citation + golden docs, so it is open-book verifiable… See the full description on the dataset page: https://huggingface.co/datasets/ranjithraj/cancer-knowledge-base.specialist-level_medical_knowledge_dataset_sft
specialist-level_medical_knowledge_dataset_sft
Dataset Summary
specialist-level_medical_knowledge_dataset_sft is an integrated collection of augmented SFT data across 13 distinct medical domains, developed by the Healthcare AI Research Institute (HARI) at SNUH.
This dataset is derived and augmented from the Specialized Medical Knowledge Data (전문 의학지식 데이터) provided by AI-Hub.
It focuses exclusively on complex clinical scenarios generated using the "Add Constraints"… See the full description on the dataset page: https://huggingface.co/datasets/snuh/specialist-level_medical_knowledge_dataset_sft.python-image-copilot-training-using-class-knowledge-graphs-2024-01-27
Python Copilot Image Training using Class Knowledge Graphs
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 a png file in the dbytes column.
Rows: 312836
Size: 294.1 GB
Data type: png
Format: Knowledge graph using NetworkX with alpaca text box
Schema
The png is in the dbytes column:
{
"dbytes": "binary"… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-image-copilot-training-using-class-knowledge-graphs-2024-01-27.Mephisto-Knowledge_538k
Mephisto-Knowledge_538k
538,861 English knowledge SFT examples generated by
Qwen/Qwen3.5-4B in non-thinking
(Instruct) mode on the Knowledge prompts of
openbmb/UltraData-SFT-2605.
Responses contain no chain-of-thought — thinking was disabled at generation
time, so each assistant turn is a direct answer, usually with a short
justification.
Companion dataset: Mephisto-IF_172k
(instruction-following, same teacher and pipeline).
Read this before training: ref_agrees… See the full description on the dataset page: https://huggingface.co/datasets/Yxanul/Mephisto-Knowledge_538k.python-image-copilot-training-using-function-knowledge-graphs
Python Copilot Image Training using Function Knowledge Graphs
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 a png file in the dbytes column.
Rows: 134357
Size: 130.5 GB
Data type: png
Format: Knowledge graph using NetworkX with alpaca text box
Schema
The png is in the dbytes column:
{
"dbytes": "binary"… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-image-copilot-training-using-function-knowledge-graphs.global-seo-knowledgemultilingual-knowledge-training-pool
Multilingual knowledge training pool
Public multiple-choice questions in many languages from seven datasets, read at the pinned
revisions named below and laid out twice. Train on either layer or on both.
pool.jsonl
Every source rewritten into one shape, 328665 rows in 116 languages, one JSON object per line,
with these fields.
Field
What it holds
id
a row identifier unique within this file
question
the question text, as its source publishes it… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/multilingual-knowledge-training-pool.auxiliary-views-knowledge-acquisition
Auxiliary Views Knowledge Acquisition
This repository contains the cleaned source documents and evaluation
probes used in Knowledge Acquisition During Pre-training? Large Language Models
Learn Better With Auxiliary Views (arXiv:2609.04180).
News
August 21, 2026: Our paper was accepted to Findings of EMNLP 2026.
Configurations
Configuration
Split
Rows
documents
train
30
factual_cloze
test
6,435
factual_mcqa_5shot
test
4,515… See the full description on the dataset page: https://huggingface.co/datasets/jiosephlee/auxiliary-views-knowledge-acquisition.knowledge_consistency_of_LLMs
What it is:
Each dataset in this delivery is made up of query clusters that test an aspect of the consistency of the LLM knowledge about a particular domain. All the questions in each
cluster are meant to be answered either 'yes' or 'no'. When the answers vary within a cluster, the knowledge is said to be inconsistent. When all the questions in a cluster
are answered 'no' when the expected answer is 'yes' (or viceversa), the knowledge is said to be 'incomplete' (i.e., maybe the LLM… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/knowledge_consistency_of_LLMs.chemistry-knowledge
ChemBricks Knowledge
Does caffeine prefer water or an oil-like liquid?Why can adding one small group change a molecule's behavior?Can we design a molecule that interacts more favorably with water while meeting other constraints?How much energy does it take to remove an electron from a molecule?
These are the kinds of questions behind this dataset. Each investigation connects a question to recorded calculations, an answer, and the evidence needed to examine that answer.
Created… See the full description on the dataset page: https://huggingface.co/datasets/chembricks/chemistry-knowledge.delvantic-stock-knowledge-layer
Delvantic Stock Knowledge Layer
A 872k-word, source-cited textbook of stock analysis and trading, organized as a tree —
the reference layer behind a live AI research engine, published in full.
Every finance dataset on the Hub is numbers: prices, filings, labelled headlines. This is the
missing other half — the explanations. 771 documents on how the machinery of markets
actually works, from reading a cash-flow statement to why volatility regimes break strategies,
each one written… See the full description on the dataset page: https://huggingface.co/datasets/fatcat55/delvantic-stock-knowledge-layer.peka_persian_knowledge_assessment
PeKA (Persian Knowledge Assessment)
PeKA is a dataset introduced in the paper "Advancing Persian LLM Evaluation", accepted at NAACL 2025 findings. It was developed as part of a broader effort to evaluate and benchmark large language models (LLMs) for multiple Persian knowledge topics.
For comprehensive details regarding the dataset’s construction, scope, task, and intended use, please refer to the original paper.
This dataset is constructed so that answering these questions… See the full description on the dataset page: https://huggingface.co/datasets/MatinaAI/peka_persian_knowledge_assessment.essential-level_medical_knowledge_dataset_sft
essential-level_medical_knowledge_dataset_sft
Dataset Summary
essential-level_medical_knowledge_dataset_sft is an integrated collection of augmented SFT data across 4 distinct medical domains, developed by the Healthcare AI Research Institute (HARI) at SNUH.
This dataset is derived and augmented from the Essential Medical Knowledge Data (필수의료 의학지식 데이터) provided by AI-Hub.
It focuses exclusively on complex clinical scenarios generated using the "Add Constraints"… See the full description on the dataset page: https://huggingface.co/datasets/snuh/essential-level_medical_knowledge_dataset_sft.Dataset-For-Indian-legal-knowledge-base About This Dataset
This dataset is the knowledge backbone of LegalEagle — an AI-powered contract review platform for Indian startups and freelancers. It contains Indian statutes, contract templates, landmark case references, and clause examples, curated specifically for retrieval-augmented generation (RAG) in the Indian legal domain.
All government statutes included are in the public domain (Government of India publications).
Dataset Structure
dataset/
├── acts/… See the full description on the dataset page: https://huggingface.co/datasets/d-riti/Dataset-For-Indian-legal-knowledge-base.nemiling-knowledge-base
Nemiling Knowledge Base
Nemiling Knowledge Base is the official structured knowledge dataset about Nemiling.
Nemiling is a Russian platform for automating the monetization of Telegram projects through paid subscriptions, paid messages, paid consultations, and donations.
The platform can be used for projects with Russian and international audiences.
The dataset is maintained by the official Nemiling organization and provides structured, machine-readable information about the… See the full description on the dataset page: https://huggingface.co/datasets/nemiling-official/nemiling-knowledge-base.oran_spec_knowledge_graph
🌐 Knowledge Graph for Open Radio Access Network (O-RAN)
A large-scale, semantically grounded knowledge graph built from O-RAN Alliance specifications,designed to enhance LLM reasoning and retrieval for next-generation telecom systems.
Overview • Motivation • Dataset Details • Getting Started • Use Cases
Overview
O-RAN (Open Radio Access Network) is an industry-driven paradigm for designing mobile networks with open, interoperable interfaces and intelligent… See the full description on the dataset page: https://huggingface.co/datasets/GSMA/oran_spec_knowledge_graph.omnimcp_graphrag_knowledge_teaser
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📜 Enterprise Compliance: EU AI Act Articles 50 & 53 certified • 100% DSGVO / GDPR clean • Commercial EULA… See the full description on the dataset page: https://huggingface.co/datasets/emgena/omnimcp_graphrag_knowledge_teaser.SA-Knowledge
SA-Knowledge
This repository collects corpora and evaluation data for four South African
languages: isiZulu, isiXhosa, Sepedi and Sesotho. The resources were developed
for the doctoral thesis Injecting Commonsense Knowledge into Pretrained
Language Models for Low Resource Languages (University of Cape Town, 2026).
Each subset corresponds to a thesis chapter and can be used independently.
Point of contact: Sello Ralethe
Supervisor: Dr. Jan Buys, Department of Computer Science… See the full description on the dataset page: https://huggingface.co/datasets/sello-ralethe/SA-Knowledge.pharos-knowledge-packs
Pharos Knowledge Pack Library
Zero-token domain expertise for open-weight language models.
108 packs | 5,700+ triples | 50 US states covered | Verified with source URLs
What Are Pharos Packs?
Walk-encoded knowledge graphs designed for injection into a model's KV cache at inference time. No fine-tuning, no retraining, no API calls. The model gains domain expertise in milliseconds, and the packs work across any open-weight architecture.
Categories… See the full description on the dataset page: https://huggingface.co/datasets/LiberationLabs/pharos-knowledge-packs.