datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tests-raw-jsonlraw_jsonlwsinfer-model-zoo-jsonThis is the registry of models in the WSInfer Model Zoo.
See https://wsinfer.readthedocs.io/en/latest/ and https://github.com/SBU-BMI/wsinfer-zoo for more information.
ner-jsonlformat-jsonformat-jsonlwdc-common-crawl-embedded-jsonldJSONSchemaBench
JSONSchemaBench
JSONSchemaBench is a benchmark of real-world JSON schemas designed to evaluate structured output generation for Large Language Models (LLMs). It contains approximately 10,000 JSON schemas, capturing diverse constraints and complexities.
import datasets
from datasets import load_dataset
def main():
# Inspect the available subsets of the datasetall_subsets = datasets.get_dataset_config_names("epfl-dlab/JSONSchemaBench")
print("Available subsets:"… See the full description on the dataset page: https://huggingface.co/datasets/epfl-dlab/JSONSchemaBench.doc-formats-jsonl-1
[doc] formats - jsonl - 1
This dataset contains one jsonl file at the root.
gsm8k-json
Dataset Card for "gsm8k-json"
More Information needed
sharegpt-quizz-generation-json-output
ShareGPT-Formatted Dataset for Quizz Generation in Structured JSON Output
Dataset Description
This dataset is formatted in the ShareGPT style and is designed for fine-tuning large language models (LLMs) to generate quizz in structured JSON outputs. It consists of multi-turn conversations where each response follows a predefined JSON schema, making it ideal for training models that need to produce structured data in natural language scenarios.
Usage
This dataset… See the full description on the dataset page: https://huggingface.co/datasets/Arun63/sharegpt-quizz-generation-json-output.stackexchange_titlebody_best_and_down_voted_answer_jsonlThis new dataset is designed to solve this great NLP task and is crafted with a lot of care.SciLaD-all-json-v1
SciLaD (JSON)
SciLaD is a novel, large-scale dataset of scientific language constructed entirely using open-source frameworks and publicly available data sources. It comprises a curated English split containing over 10 million scientific publications and a multilingual, unfiltered TEI XML split including more than 35 million publications. We also publish the extensible pipeline for generating SciLaD.
Dataset Details
In this repository we share the full… See the full description on the dataset page: https://huggingface.co/datasets/scilons/SciLaD-all-json-v1.sharegpt-structured-output-json
ShareGPT-Formatted Dataset for Structured JSON Output
Dataset Description
This dataset is formatted in the ShareGPT style and is designed for fine-tuning large language models (LLMs) to generate structured JSON outputs. It consists of multi-turn conversations where each response follows a predefined JSON schema, making it ideal for training models that need to produce structured data in natural language scenarios.
Usage
This dataset can be used to train LLMs… See the full description on the dataset page: https://huggingface.co/datasets/Arun63/sharegpt-structured-output-json.stackexchange_title_best_voted_answer_jsonlThis new dataset is designed to solve this great NLP task and is crafted with a lot of care.hermes-function-calling-v1-jsonl
Hermes Function-Calling V1
This dataset is the compilation of structured output and function calling data used in the Hermes 2 Pro series of models.
This repository contains a structured output dataset with function-calling conversations, json-mode, agentic json-mode and structured extraction samples, designed to train LLM models in performing function calls and returning structured output based on natural language instructions. The dataset features various conversational scenarios… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/hermes-function-calling-v1-jsonl.desktop-accessibility-screenshot-json-dumpsjson-mode-evalstackexchange_title_body_jsonljsonl.gz format from https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_xml
Each line contains a dict in the format: {"text": ["title", "body"], "tags": ["tag1", "tag2"]}
The following parameters have been used for filtering: min_title_len = 20 min_body_len = 20 max_body_len = 4096 min_score = 0
If a stackexchange contained less than 10k questions (after filtering), it is written to the small_stackexchanges.jsonl.gz file.
This is a dump of the files from… See the full description on the dataset page: https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_title_body_jsonl.conceptual_captions_jsonstackexchange_titlebody_best_voted_answer_jsonlThis new dataset is designed to solve this great NLP task and is crafted with a lot of care.Sheetpedia_json_1005TravelUAV_data_jsonmidi-classical-music-toio-json
MIDI Classical Music
drengskapur/midi-classical-musicのデータセットをtoioの soundコマンドで再生しやすいように以下のフォーマットのjsonに変換したデータを含めたデータセット
data format
[
{
"track_name": "ALBENIZ: Aragon Op 47/6",
"priority": 1,
"notes": [
{
"note_number": 77,
"start_time_ms": 0,
"duration_units": 26
},
{
},
},
{
"track_name": "apurdam@pcug.org.au",
"priority": 2,
"notes": [
{
"note_number": 53,
"start_time_ms": 0… See the full description on the dataset page: https://huggingface.co/datasets/ayousanz/midi-classical-music-toio-json.Sheetpedia_json_files_1005auditbench-viz-jsonjson-mode-eval-extended
JSON-Mode-eval extended
This is a dataset that measures LLM capabilities at extracting data from natural language following a JSON Schema.
It was generated by manually cleaning and normalizing json-mode-eval by Nous-Research, which resulted in json-mode-eval-cleaned, ensuring that every schema enforces non-empty constraints and allow no additional keys on the top level.
We then prompt Gemini 2.5 Pro for additional 10 samples per schema, filtering for outputs that are valid according… See the full description on the dataset page: https://huggingface.co/datasets/eth-sri/json-mode-eval-extended.stackexchange_math_jsonlThis new dataset is designed to solve this great NLP task and is crafted with a lot of care.pseudo-camera-10k-structured-json
pseudo-camera-10k, structured JSON captions
The 9,997 training images from bghira/pseudo-camera-10k, recaptioned into the structured JSON caption schema that Ideogram 4 consumes. The images are unchanged: free photographs from world class photographers, Lanczos-resized so the shorter edge is 1024px, nothing upsampled.
The original dataset carries short CogVLM prose captions. This one replaces them with one JSON object per image describing the scene at three levels: an overall… See the full description on the dataset page: https://huggingface.co/datasets/terminusresearch/pseudo-camera-10k-structured-json.Ascend-COT-v2-json
AscendKernelGen/Ascend-COT-v2-json
AscendKernelGen/Ascend-CoT-v2-json contains a subset of the full Ascend-CoT dataset, which will be released in stages. The Ascend-CoT Dataset is a high-quality, domain-specific dataset that incorporates Chain-of-Thought (CoT) reasoning derived from real-world kernel implementations. It combines three types of reasoning: documentation-based reasoning, code-centric reasoning extracted from actual NPU kernel code, and general reasoning chains that… See the full description on the dataset page: https://huggingface.co/datasets/AscendKernelGen/Ascend-COT-v2-json.