datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
single-cell-brain-zarr
Single-Cell Brain Zarr Collection
Production-ready brain single-cell RNA-seq data exported from the CellxGene Census into native Zarr stores for chunked, on-demand access on the Hugging Face Hub.
Why Zarr
Single-cell expression matrices get impractical fast if you treat them like ordinary dense files. Zarr is the point of this repo: it makes large atlas-scale data usable without forcing users to download or materialize the whole matrix before they can do anything useful.… See the full description on the dataset page: https://huggingface.co/datasets/KokosDev/single-cell-brain-zarr.RadGenome-Brain_MRI_parquetszl-second-brain-inrepo
SZL Second Brain — in-repo lane (public projection)
This is DATA, not a model. A retrieval corpus — the in-repo lane of the
SZL Second Brain — published as a Hugging Face dataset. It is part of the
SZL Forge Family. Publishing it is repo-existence of a corpus only: it
trains nothing, evaluates nothing, serves no inference, and upgrades nothing
(Λ stays Conjecture-1).
What this is
A deterministic BM25-ready corpus assembled only from repo-public text of
the Alloy… See the full description on the dataset page: https://huggingface.co/datasets/SZLHOLDINGS/szl-second-brain-inrepo.TopoSense-Bench
TopoSense-Bench: A Campus-Scale Benchmark for Semantic-Spatial Sensor Scheduling
TopoSense-Bench is a large-scale, rigorous benchmark designed to evaluate Large Language Models (LLMs) and agents on the Semantic-Spatial Sensor Scheduling (S³) problem. It features a realistic digital twin of a university campus equipped with 2,510 cameras and contains 5,250 natural language queries grounded in physical topology.
This dataset is the official benchmark for the ACM MobiCom 2026 paper:… See the full description on the dataset page: https://huggingface.co/datasets/IoT-Brain/TopoSense-Bench.test-braindecode-integration
EEG Dataset
This dataset was created using braindecode, a library for deep learning with EEG/MEG/ECoG signals.
Dataset Information
Number of recordings: 1
Number of channels: 26
Sampling frequency: 250.0 Hz
Data type: Windowed (from Epochs object)
Number of windows: 48
Total size: 0.04 MB
Storage format: zarr
Usage
To load this dataset:
from braindecode.datasets import BaseConcatDataset
# Load dataset from Hugging Face Hub
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Kkuntal990/test-braindecode-integration.brain-memory
🧠 NIFTY AI Agent: Memory OS Cloud Snapshot
Cloud backup repository for the NIFTY 50 Autonomous AI Agent Memory OS.
• Repository: nagarhimanshu37/brain-memory• Total Stored Records: 217• Last Synchronized: 2026-09-23 12:34:52 UTC
📊 Partition Statistics
Partition
Records
Description
conversation_memory
70
Multi-turn trader dialogues & intent logs
episodic_memory
50
Trading day episodes (facts vs interpretations)
experience_memory
50
Crystallized… See the full description on the dataset page: https://huggingface.co/datasets/nagarhimanshu37/brain-memory.RadGenome-Brain_MRIbrainteasercode-training-il
Code-Training-IL
A 40,330-example instruction-tuning dataset for code: 20K Python (NVIDIA OpenCodeInstruct, test-filtered) + 20K TypeScript + 330 hand-written bilingual identity examples.
Overview
code-training-il is a curated, filtered instruction-tuning corpus for training small coding assistants. It is the dataset used to fine-tune code-il-E4B, a 4B on-device model.
The dataset was designed around a thesis: less data, better filtered, beats more data. The… See the full description on the dataset page: https://huggingface.co/datasets/BrainboxAI/code-training-il.ixi-brainmedical-training-il
Medical-Training-IL
A bilingual (Hebrew / English) medical instruction-tuning corpus — curated for training small, on-device medical models for Israeli residents preparing for Stage A exams.
Overview
medical-training-il is a curated, bilingual medical instruction-tuning dataset designed to fine-tune language models for Israeli clinical reasoning. It combines high-quality English medical QA (USMLE-style, basic sciences, research-grounded) with ~5,000 Hebrew-native… See the full description on the dataset page: https://huggingface.co/datasets/BrainboxAI/medical-training-il.brainly
brainly.co.id dataset
Data Structure
The keys in each JSONL object include:
"id": An integer value representing the page of task from url (e.g. brainly.co.id/tugas/117).
"subject": A string indicating the subject of the question (e.g., "Fisika", "Matematika", "Sejarah").
"author": A string representing the author of the question.
"instruction": A string providing the instruction or prompt for the question.
"answerer_1", "answer_2": Strings representing the answerers for… See the full description on the dataset page: https://huggingface.co/datasets/lesserfield/brainly.uv-brain-s03_custom_with_rehearsalswebench-django
SWE-bench Django (30-task subset)
Thirty real bug-fix tasks from the Django project, derived from SWE-bench (Jimenez, Yang, et al., ICLR 2024). Each task is a merged pull request rewound to its buggy commit: an agent gets only the issue text, must locate and fix the bug in the codebase, and the fix is checked against the PR's held-out test.
This subset powers a Braintrust eval on behavior-vs-output scoring — whether a coding agent obeys a "locate code via vector search only"… See the full description on the dataset page: https://huggingface.co/datasets/BraintrustDataDev/swebench-django.uv-brain-s03_custom_with_rehearsal_v2example_dataset-raw
EEG Dataset
This dataset was created using braindecode, a deep
learning library for EEG/MEG/ECoG signals.
Dataset Information
Property
Value
Recordings
1
Type
Continuous (Raw)
Channels
26
Sampling frequency
250 Hz
Total duration
0:06:26
Windows/samples
96,735
Size
19.22 MB
Format
zarr
Quick Start
from braindecode.datasets import BaseConcatDataset
# Load from Hugging Face Hub
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/braindecode/example_dataset-raw.big-braincode
# used when training samples do not include a system prompt.
DEFAULT_SYSTEM_PROMPT = "Below is an instruction that describes a task. Write a response that appropriately completes the request."
# did not add item to dataset if prompt or system prompt contains any of these bad words.
# if any of these words are in the system or prompt, the item will be skipped.
BAD_WORDS = [
"english", "translate", "translation", "russian", "chinese", "japanese", "spanish", "persian", "french", "german"… See the full description on the dataset page: https://huggingface.co/datasets/perlthoughts/big-brain.brainstorming-ideation-sft-100k
Brainstorming and Ideation SFT (100K)
100,000 ShareGPT conversations demonstrating structured, high-quality brainstorming and ideation across 22 professional domains. Each example takes a realistic context and constraint, then generates specific, actionable, well-reasoned ideas — not generic advice dressed as creativity.
Motivation
Brainstorming and ideation is one of the highest-value use cases for AI assistants, and one where models routinely underperform:… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/brainstorming-ideation-sft-100k.brainstorm_vicuna_1k
'Make knowledge free for everyone'
Brainstorm 1k
Synthetic discussions in Vicnua format between Human and LLM where Human brainstorming with the AI about an idea.
To guarantee the diverse discussions, I've randomly selected topic from the following dictionary (also generated by LLM):
topics_dict = {
"Business": [
"Starting a new company", "Launching a product", "Expanding into a new market",
"Creating a business plan", "Raising venture capital", "Developing a… See the full description on the dataset page: https://huggingface.co/datasets/DevQuasar/brainstorm_vicuna_1k.uv-brain-s03_customPashto-Brain-Extraction-Dataset
🧠 Pashto Brain Extraction Dataset
A small experimental Pashto reasoning dataset designed to extract and preserve useful model reasoning/planning while discarding the final answer.
Keep the brain 🧠 — throw away the mouth 🗣️
🎯 Purpose
A language model may understand a question and produce useful reasoning while still generating poor, unnatural, or grammatically incorrect Pashto in its final answer.
Instead of throwing away the entire generation, this dataset… See the full description on the dataset page: https://huggingface.co/datasets/nassimjp/Pashto-Brain-Extraction-Dataset.tigerbot-dolly-Brainstorming-en-1.7kTigerbot 基于dolly数据集加工的头脑风暴Brainstorming相关分类的的sft。
原始来源：https://huggingface.co/datasets/databricks/databricks-dolly-15k
databricks-dolly-15k is an open source dataset of instruction-following records generated by thousands of Databricks employees in several of the behavioral categories outlined in the InstructGPT paper
Usage
import datasets
ds_sft = datasets.load_dataset('TigerResearch/tigerbot-dolly-Brainstorming-en-1.7k')
brainstorm-v3.1-grok-4-fast-200xThe responses for this dataset were generated with grok 4 fast.
Original dataset: https://huggingface.co/datasets/DevQuasar/brainstorm-v3.1_vicnua_1k
braindao__Qwen2.5-14B-Instruct-details
Dataset Card for Evaluation run of braindao/Qwen2.5-14B-Instruct
Dataset automatically created during the evaluation run of model braindao/Qwen2.5-14B-Instruct
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 3 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 results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/braindao__Qwen2.5-14B-Instruct-details.braindao__DeepSeek-R1-Distill-Qwen-14B-ABUB-ST-details
Dataset Card for Evaluation run of braindao/DeepSeek-R1-Distill-Qwen-14B-ABUB-ST
Dataset automatically created during the evaluation run of model braindao/DeepSeek-R1-Distill-Qwen-14B-ABUB-ST
The dataset is composed of 38 configuration(s), each one corresponding 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/open-llm-leaderboard/braindao__DeepSeek-R1-Distill-Qwen-14B-ABUB-ST-details.ptv3-bericht-lora-de-300
ptv3-bericht-lora-de-300
Synthetic German dataset for fine-tuning LLMs to generate structured psychotherapy reports (PTV-3 / Bericht an den Gutachter) from therapy session transcripts.
Overview
Property
Value
Samples
311 (280 train / 31 val)
Language
German
Format
ChatML JSONL (system / user / assistant)
Teacher model
Qwen2.5-27B (local)
Generation
Two-stage: seed → session transcript → PTV-3 JSON report
Schema
Each sample… See the full description on the dataset page: https://huggingface.co/datasets/speed-brain-ai/ptv3-bericht-lora-de-300.Explore_Instruct_Brainstorming_10k
Explore-Instruct: Enhancing Domain-Specific Instruction Coverage through Active Exploration
| 📑 Paper |
🤗 Data |
🤗 Model |
🐱 Github Repo |
Fanqi Wan†, Xinting Huang‡, Tao Yang†, Xiaojun Quan†, Wei Bi‡, Shuming Shi‡
† Sun Yat-sen University,
‡ Tencent AI Lab
News
Oct 16, 2023: 🔥 We're excited to announce that the Explore-Instruct datasets in brainstorming, rewriting, and math domains are now available on 🤗 Huggingface Datasets! Additionally, we've… See the full description on the dataset page: https://huggingface.co/datasets/Wanfq/Explore_Instruct_Brainstorming_10k.brain-teaser-chinesebrainblast-verified-footgun-corpus
Brainblast — Verified SDK Footgun Corpus (free sample)
The only code-training data that ships with a machine-checkable proof. Each
record is a real insecure→fixed code footgun with a replayable RED→GREEN
receipt: a deterministic checker fails the insecure version and passes the fixed
one. You don't trust the labels — you replay the proof.
This repo is a free 40-record sample (receipt-only tier). The full corpus is
4,183 proven records across 154 SDKs and 9 vulnerability classes… See the full description on the dataset page: https://huggingface.co/datasets/dsb117/brainblast-verified-footgun-corpus.spicy-brainrot-prompts
Spicy Brainrot Prompts Dataset
This dataset contains a 10-day series of high-detail image generation prompts, NSFW elements breakdown, and brainrot vibe categorization.
Dataset Structure
day: Day index (1 to 10)
theme: Theme of the prompt
prompt: Full text-to-image prompt string
nsfw_elements: List of specific elements featured
brainrot_vibe: Style/vibe summary tagline