datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
spider-text-to-sql
Spider Text-to-SQL with LLM-Judge Labels
This dataset extends Spider 1.0 with SQL predictions from gpt-5.4-mini and two correctness labels per example: a hybrid ground truth label and an LLM judge label from gpt-5.4.
Files
File
Description
spider_dataset.parquet
Full dataset with predictions and labels
scripts/
Reproduction scripts (see below)
Dataset statistics
Source: Spider 1.0 training split (train_spider.json)
Databases: the… See the full description on the dataset page: https://huggingface.co/datasets/Glide-py/spider-text-to-sql.SPIEval
SPIEval
SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information
SPIEval is a human-curated benchmark for evaluating whether large language models can act as mobile assistants by proactively retrieving and reasoning over personal information scattered across multiple applications. Given an underspecified user instruction, a model must search structured records, recover the information required for execution, and invoke the appropriate… See the full description on the dataset page: https://huggingface.co/datasets/Junjie-Ye/SPIEval.spivavtor
Dataset Card for Spivavtor
Paper: Spivavtor: An Instruction Tuned Ukrainian Text Editing Model
Authors: Aman Saini, Artem Chernodub, Vipul Raheja, Vivek Kulkarni
Dataset Summary
This is the dataset used to train all Spivavtor models. It contains data for 4 tasks - Grammatical Error Correction (GEC), Simplification, Coherence and Paraphrasing.
The specific details are as follows:
Task
Examples in Training data
Examples in Validation… See the full description on the dataset page: https://huggingface.co/datasets/grammarly/spivavtor.text-to-sql-spider-dataset
Text-to-SQL Dataset
A curated dataset for training text-to-SQL models. This dataset contains natural language questions paired with corresponding SQL queries, formatted for instruction fine-tuning.
📊 Dataset Summary
Total Samples: 20000
Format: Chat template (system/user/assistant messages)
Task: Text-to-SQL generation
Language: English
License: apache-2.0
📁 Dataset Structure
Data Format
Each example contains a conversation with three roles:… See the full description on the dataset page: https://huggingface.co/datasets/chrisjcc/text-to-sql-spider-dataset.ltspice-spice-circuits
LTspice Netlist ↔ ASC Schematic Dataset
SPICE netlists paired with their corresponding LTspice .asc schematic files,
scraped from public GitHub repositories.
Columns
netlist (string): SPICE netlist content
asc (string): Corresponding LTspice .asc schematic file content
Splits
train: 53000 samples
test: 2790 samples
Usage
from datasets import load_dataset
ds = load_dataset("Si7li/ltspice-spice-circuits")
sample = ds['train'][0]
print("Netlist:"… See the full description on the dataset page: https://huggingface.co/datasets/Si7li/ltspice-spice-circuits.delusioneval
DelusionEval
Dataset Summary
DelusionEval is an anonymized conversational evaluation dataset for measuring problematic chatbot behavior in delusional-spiral contexts.
This release contains 725 conversation windows with:
eval_subset_id (string)
label (target behavior code)
meets_code (bool)
messages (ordered list of message structs with role, content, and per-message score fields)
Supported Tasks
Safety evaluation and auditing of conversational… See the full description on the dataset page: https://huggingface.co/datasets/spiralsafety/delusioneval.spice-circuits-finetune-v2
SPICE Circuits Fine-tune V2
A clean, validated dataset of 7,410 instruction-output pairs for fine-tuning language models to generate SPICE netlists from natural language descriptions.
Dataset Description
This is Version 2 of the SPICE circuits fine-tuning dataset. V1 was polluted with mixed formats (LTspice, KiCad, standard SPICE) and no validation. V2 is fully validated — every netlist passes PySpice's SpiceParser.build_circuit() gate. No exceptions.… See the full description on the dataset page: https://huggingface.co/datasets/ADI2005/spice-circuits-finetune-v2.spider-dpo-1040
Spider DPO 1040
Spider DPO 1040 is a compact Text-to-SQL training dataset for supervised fine-tuning and Direct Preference Optimization. It contains 1,040 preference pairs derived from frontier-model disagreements on Spider V1, plus 7,000 supervised Spider train examples formatted for LLaMA-Factory.
The dataset was created for the companion LoRA adapter jk200201/qwen2.5-coder-7b-sql-dpo.
Important Evaluation Note
The DPO preference pairs in this repository were… See the full description on the dataset page: https://huggingface.co/datasets/jk200201/spider-dpo-1040.spider2-aifuncSpider2-AIFunc
A benchmark for AI-Native Text-to-SQL with Snowflake Cortex AISQL
Spider2-AIFunc extends Spider 2.0 and Spider2-Snow with real-world tasks that require Snowflake Cortex AISQL functions inside SQL queries.
This dataset contains the released task metadata:
data/spider2-aifunc.jsonl: 393 tasks with natural-language instructions, database IDs, target AISQL functions, external-knowledge references, and evaluation configs.
Gold SQL, gold execution results… See the full description on the dataset page: https://huggingface.co/datasets/tianyang/spider2-aifunc.SPICE-Circuitsmascarade-spice-dataset
Ailiance — SPICE & Analog Simulation Q&A
🇫🇷 Ailiance — curated by Ailiance for production deployment ; co-published with the upstream electron-rare/mascarade-spice-dataset. 🇪🇺 Compatible EU AI Act (Template AI Office, July 2025).
Q&A bilingue (FR/EN) sur la simulation SPICE et l'analyse de circuits analogiques : ngspice, LTspice, modèles MOSFET/BJT, topologies analogiques, ampli-op, filtres actifs, sources de courant, polarisation.
Statistics
Métrique… See the full description on the dataset page: https://huggingface.co/datasets/Ailiance-fr/mascarade-spice-dataset.ficbook_top1Subset of ficbook dataset. Top 1 fanfic by likes for each category in first 16 parts of dataset.
mascarade-spice-dataset
Mascarade — SPICE & Analog Simulation Q&A
Description
Q&A bilingue (FR/EN) sur la simulation SPICE et l'analyse de circuits analogiques : ngspice, LTspice, modèles MOSFET/BJT, topologies analogiques, ampli-op, filtres actifs, sources de courant, polarisation.
Ce dataset fait partie de la famille Mascarade, un corpus thématique destiné au fine-tuning LoRA de modèles compacts (cible : Gemma-3n-E4B et équivalents) pour des assistants spécialisés en électronique embarquée.… See the full description on the dataset page: https://huggingface.co/datasets/electron-rare/mascarade-spice-dataset.deep-comparative-spirituality-zh
Deep Comparative Spirituality Studies Dialogue Dataset (Chinese)
深度比较灵性研究对话数据集
Dataset Description
High-quality Chinese comparative spirituality dialogues covering Kabbalah Tree of Life, Jungian psychology and mysticism, Tarot symbolism, and East-West spiritual traditions.
高质量中文比较灵性研究对话，涵盖卡巴拉生命树、荣格心理学与神秘学交叉、塔罗象征体系、东西方灵性传统比较等议题。
Dataset Structure
Format: JSONL (JSON Lines)
Fields:
instruction: User message / question
input: Additional… See the full description on the dataset page: https://huggingface.co/datasets/AngelWarmSmile123/deep-comparative-spirituality-zh.ltspice-spice-circuits-no-aug
LTspice Netlist ↔ ASC Schematic Dataset
SPICE netlists paired with their corresponding LTspice .asc schematic files,
scraped from public GitHub repositories.
Columns
netlist (string): SPICE netlist content
asc (string): Corresponding LTspice .asc schematic file content
Splits
train: 7866 samples
test: 414 samples
Usage
from datasets import load_dataset
ds = load_dataset("Si7li/ltspice-spice-circuits-no-aug")
sample = ds['train'][0]… See the full description on the dataset page: https://huggingface.co/datasets/Si7li/ltspice-spice-circuits-no-aug.spider-text2sql-bench
Dataset Card for spider-text2sql-bench
spider-text2sql-bench 是 Spider 1.0 官方訓練集之 OpenAI Messages 格式版本，共 7,000 筆，將原始之 question / schema / sql 重新組裝為 system / user / assistant 三 role 之對話結構。除原生之 messages 欄位外，另拆解出獨立之 system / user / assistant 字串欄位，可作為 Text-to-SQL 模型之 SFT 訓練語料，亦可直接用於 benchmark evaluation pipeline（以 user 作為 prompt，比對模型輸出與 assistant 之標準答案 SQL）。
Dataset Details
Dataset Description
Spider 1.0 為 Yale LILY Group 於 EMNLP 2018 發表之大規模跨領域 Text-to-SQL… See the full description on the dataset page: https://huggingface.co/datasets/lianghsun/spider-text2sql-bench.dbbench-spider-3500
DBBench-Spider-3500
AgentBench DBBench 評価ハーネスと完全互換のフォーマットで生成した SFT 訓練データセット。
Spider データセット (Yale NLP) の 3,500 問を GPT-OSS-120B (Groq) に解かせ、正解したトラジェクトリ 1,697 件 を収録。
混合利用を想定: 本データセットは mark-22/dbbench_cleaned_for_agentbench（1,200 件）と混合し、合計 2,897 件 の SFT データとして使用することを想定しています。
Dataset Summary
Metric
Value
Total trajectories
1,697
Difficulty: Medium
1,406
Difficulty: Hard
291
Avg messages per item
13.2
Unique databases (db_id)
159
Source questions3… See the full description on the dataset page: https://huggingface.co/datasets/mark-22/dbbench-spider-3500.querysmith-spider-bird
querysmith-spider-bird
Schema-grounded text-to-SQL training data used to fine-tune
ajayk007/Qwen2.5-Coder-7B-Querysmith.
~13.7k examples derived from Spider and
BIRD.
Format
mlx-lm chat format, one example per line:
{"messages": [
{"role": "system", "content": "You are a text-to-SQL generator ..."},
{"role": "user", "content": "Schema:\nCREATE TABLE ...\n\nQuestion: ..."},
{"role": "assistant", "content": "SELECT ..."}
]}
The user turn contains the… See the full description on the dataset page: https://huggingface.co/datasets/ajayk007/querysmith-spider-bird.Bangla-SFT-50k
Bangla-SFT
Bangla-SFT is an instruction-following dataset containing 50,053 Bengali prompt-response pairs. It was scaled up from a 500-sample seed dataset (spitfire4794/bang_seed).
Dataset Summary
The dataset covers 6 task categories. The prompts are designed to be self-contained (hydrated with appropriate contextual inputs), and the responses are formatted to be direct, omitting conversational prefaces and filler.
Seed Generation: Baseline instructions generated… See the full description on the dataset page: https://huggingface.co/datasets/spitfire4794/Bangla-SFT-50k.Spiral-Kuhn-Poker-Qwen3-32B-SFT
Spiral-Kuhn-Poker-Qwen3-32B-SFT
Links
📜 Paper
💻 GitHub
🤗 Spiral Collection
Introduction
This expert dataset is collected by keeping the winning trajectories of self-play using Qwen3-32B on Kuhn Poker. It is part of the SPIRAL: Self-Play on Zero-Sum Games Incentivizes Reasoning via Multi-Agent Multi-Turn Reinforcement Learning project. SPIRAL is a self-play framework where models learn by playing multi-turn, zero-sum games against continuously improving… See the full description on the dataset page: https://huggingface.co/datasets/spiral-rl/Spiral-Kuhn-Poker-Qwen3-32B-SFT.cyberstrike-sft-120k
CyberStrike SFT 120K
The largest open-source offensive cybersecurity SFT dataset
121,422 expert-level red team instruction-response pairs across 15 security generators
Quick Start •
Why CyberStrike •
Domains •
Data Format •
Training Guide •
Benchmarks •
Contributing •
License
Why CyberStrike?
Most LLMs refuse or give surface-level answers to offensive security questions. Security professionals —… See the full description on the dataset page: https://huggingface.co/datasets/spinochenza/cyberstrike-sft-120k.spicyfictionchannel_postsSpirit_Kings_Golden_Textbook
About
This is a dataset about the Spirit Kings clan from the Mineberry Minecraft server.
Deepthinking-alfworld_and_dbbench_spider_v2
Deepthinking ALFWorld & DBBench Spider v2
AgentBench 評価の 2 タスク（ALFWorld / DBBench）を統合した マルチタスク SFT 訓練データセット。
フォーマット検査・フィルタリング済みの 7,779 件を、サイズ比率に基づく等間隔インターリーブで結合。
Dataset Summary
Metric
Value
Total rows
7,779
ALFWorld
4,884 (62.8%)
DBBench
2,895 (37.2%)
Avg messages per item
18.3
Columns
messages
Interleave method
比率ベース等間隔マージ
Source Datasets
Source
Rows
Description
mark-22/Deepthinking-sft_alfworld_final1
4,884
ALFWorld… See the full description on the dataset page: https://huggingface.co/datasets/mark-22/Deepthinking-alfworld_and_dbbench_spider_v2.celestial-spiritual-conversations-v2
CELESTIAL Spiritual Conversations Dataset
Dataset Description
This dataset is part of the CELESTIAL spiritual AI platform, designed for training Mistral-7B models on spiritual and astrological guidance tasks.
Dataset Summary
Total Examples: 3000
Categories: spiritual_conversation
Languages: English, Hindi (transliterated)
Format: Conversational format with tool calling examples
Dataset Structure
{
"messages": [
{"role": "user", "content":… See the full description on the dataset page: https://huggingface.co/datasets/Emilynnjk/celestial-spiritual-conversations-v2.celestial-spiritual-ai-dataset
CELESTIAL Spiritual AI Training Dataset
Overview
Comprehensive spiritual AI training dataset with 190+ conversations covering all 16 CELESTIAL spiritual systems.
Features Covered
Vedic Astrology & Kundli Generation
Numerology & Life Path Analysis
Divine AI Personas (Krishna, Ganesha, Shiva, Devi, Hanuman, Saraswati)
Vastu Shastra & Palmistry
Spiritual Guidance & Meditation
And 11 more spiritual systems!
Quality Metrics
Overall Score: 94.9%… See the full description on the dataset page: https://huggingface.co/datasets/dp1812/celestial-spiritual-ai-dataset.food_json_extractDictionary of units of measurement: gram, piece, milliliter, slice, cup, glass, bowl, serving, plate, handful, side, tablespoon, teaspoon
celestial-spiritual-conversations-v2
CELESTIAL Spiritual Conversations Dataset
Dataset Description
This dataset is part of the CELESTIAL spiritual AI platform, designed for training Mistral-7B models on spiritual and astrological guidance tasks.
Dataset Summary
Total Examples: 3000
Categories: spiritual_conversation
Languages: English, Hindi (transliterated)
Format: Conversational format with tool calling examples
Dataset Structure
{
"messages": [
{"role": "user", "content":… See the full description on the dataset page: https://huggingface.co/datasets/dp1812/celestial-spiritual-conversations-v2.dbbench_spider_v4_mergeddata_final1
DBBench Spider v4 Merged Data (Final)
AgentBench DBBench 評価用の SFT 訓練データセット。
以下の 2 つのデータセットを結合した 2,897 件 の統合データ。
Source
Rows
Description
mark-22/dbbench_cleaned_for_agentbench
1,200
u-10bei/dbbench_sft_dataset_react_v4 をクレンジングしたもの
mark-22/dbbench-spider-3500
1,697
Spider 3,500 問を GPT-OSS-120B で生成し、正解のみフィルタしたもの
合計
2,897
Dataset Summary
Metric
Value
Total rows
2,897
Avg messages per item
10.5
Items with Final Answer
2,884 / 2,897… See the full description on the dataset page: https://huggingface.co/datasets/mark-22/dbbench_spider_v4_mergeddata_final1.