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.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.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.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.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.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.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.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.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.arachnia-nano-datasets
Arachnia Nano 270m
Arachnia Nano aims to be a lightweight retrieval-based context-aware proactive assistant for:
Retrieval-augmented factual autocompletion
Email auto completion
General-purpose web text completion
Suggestions
Architecture
Arachnia Nano is based on these two models:
Gemma 3 270m IT
EmbeddingGemma
We aim to bridge these two models into a single architecture to sync what generative model wants to see and what the embedding layer shows it.… See the full description on the dataset page: https://huggingface.co/datasets/spider-ai/arachnia-nano-datasets.