datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Erotic_Literature_CollectionEnglish
中文色情文学数据集合集
概述
本仓库包含了51个中文色情文学数据集。每个数据集由短篇色情小说、个人色情经验及其他形式的色情内容组成。数据集的格式为JSON，每个文件包含一个对象数组，每个对象代表一篇文档：
[
{"text": "document"},
{"text": "document"}
]
这些数据集可用于语言模型的预训练，经过适当调整后也可用于模型的微调。
数据集格式
文件格式： JSON
内容： 短篇色情小说、个人色情经验及其他色情内容
结构：
每个文件包含一个对象数组
每个对象包含一个键 "text"，其值为相应的文档内容
使用方法
这些数据集主要用于研究目的，特别是在语言模型的开发和微调中使用。由于内容的敏感性，用户应谨慎处理这些数据集，并确保遵守当地的法律法规及相关指导原则。
示例用法
import json
# 加载数据集with open('path_to_json_file.json', 'r'… See the full description on the dataset page: https://huggingface.co/datasets/ystemsrx/Erotic_Literature_Collection.Huatuo26M-Lite
Huatuo26M-Lite 📚
Table of Contents 🗂
Dataset Description 📝
Dataset Information ℹ️
Data Distribution 📊
Usage 🔧
Citation 📖
Dataset Description 📝
Huatuo26M-Lite is a refined and optimized dataset based on the Huatuo26M dataset, which has undergone multiple purification processes and rewrites. It has more data dimensions and higher data quality. We welcome you to try using it.
Dataset Information ℹ️
Dataset Name: Huatuo26M-Lite
Version:… See the full description on the dataset page: https://huggingface.co/datasets/FreedomIntelligence/Huatuo26M-Lite.LiteCoder-Terminal-SFT
LiteCoder-SFT-Terminal
Paper | Code | Blog Post
LiteCoder-SFT-Terminal is a dataset of 11,255 agent trajectories in terminal environments, introduced in the paper LiteCoder-Terminal: Scaling Long-Horizon Terminal Environments for Learning Language Agents.
Fine-tuned on this data, the LiteCoder-Terminal-30b-a3b-sft model achieves 31.5% Pass@1 on Terminal Bench Pro, while the LiteCoder-Terminal-4b-sft model shows distinct gains over its baseline.
Released Artifacts… See the full description on the dataset page: https://huggingface.co/datasets/Lite-Coder/LiteCoder-Terminal-SFT.swe-bench-lite-agent-traces-v14
AgentBRANE SWE-bench Lite Agent Traces v14
This release contains the 1,890 harness-native agent traces selected by the sealed SWE-bench Lite v14 publication record (1,379/1,890 resolved, 73.0%). It includes Claude Code, Codex, and Pi sessions across seven models and three replicates. No internal research notes are included.
Load the observation table:
from datasets import load_dataset
traces = load_dataset("melissapan/swe-bench-lite-agent-traces-v14", split="train")
Each row… See the full description on the dataset page: https://huggingface.co/datasets/melissapan/swe-bench-lite-agent-traces-v14.commongen_lite
CommonGen-Lite
Evaluating LLMs with CommonGen using CommonGen-lite dataset (400 examples + 900 human references).
We use GPT-4 to evaluate the constrained text generation ability of LLMs. Please see more in our paper.
Github: https://github.com/allenai/CommonGen-Eval
Leaderboard
model
len
cover
pos
win_tie
overall
human
12.84
99.00
98.11
100.00
97.13
gpt-4-0613
14.13
97.44
91.78
50.44
45.11
gpt-4-1106-preview14.90
96.33
90.11
50.78
44.08… See the full description on the dataset page: https://huggingface.co/datasets/allenai/commongen_lite.Ring-lite-sft-data
🤖 ModelScope
🤗 HuggingFace
🖥️ GitHub
Ring-lite-sft-data
This is a the SFT data used during the fine-tuning of the Ring-lite model. The query pool was sourced from open-source repositories and further enriched through synthetic generation using large language models (LLMs). To ensure the production of high-fidelity responses with Long-CoT, we implemented an iterative refinement pipeline that synergistically combines automated model… See the full description on the dataset page: https://huggingface.co/datasets/inclusionAI/Ring-lite-sft-data.russian_literature
RusLit Corpus
A corpus of Russian literature in clean text format.
Description
This dataset contains cleaned text (stripped of extraneous artifacts) collected from works by authors who passed away more than 70 years ago, placing them in the public domain.
Some texts may contain semantic nonsense (e.g. OCR or digitization artifacts), as well as fragments of French, German, English, or Japanese text mixed in with the Russian.
Structure
Each record… See the full description on the dataset page: https://huggingface.co/datasets/RafaelUI/russian_literature.IndustryCorpus_literature[中文主页]
Industry models play a crucial role in driving enterprise intelligence transformation and innovative development. High-quality industry data is key to improving the performance of large models and realizing industry applications. However, datasets currently used for industry model training generally suffer from issues such as insufficient data volume, low quality, and lack of domain expertise.
To address these problems, we constructed and applied 22 industry data processing operators to… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus_literature.wolne-lektury-polish-literature-corpus
Wolne Lektury Polish Literature Corpus
Dataset Description
A comprehensive corpus of Polish literary works from Wolne Lektury — a free digital library of public domain literature. All texts are in the public domain.
The corpus was collected via the official REST API (https://wolnelektury.pl/api/), including full text of each work, metadata (author, epoch, genre, kind), and language information.
Statistics
Metric
Value
Records
7,316… See the full description on the dataset page: https://huggingface.co/datasets/PiotrSty/wolne-lektury-polish-literature-corpus.Ring-lite-rl-data
🤗 Hugging Face
🤖 ModelScope
🖥️ GitHub
Ring-lite-rl-data
This dataset is a curated subset of high-quality problems across mathematics and code domains designed for reinforcement learning in the Ring-lite model. This dataset contains:
Mathematics: Over 39,000 rigorously curated problems sourced from:
Open-source datasets (BigMath, DeepScaleR, DAPO, DeepMath-103K)
Art of Problem Solving (AoPS) contest collections
Code: Approximately 8,400… See the full description on the dataset page: https://huggingface.co/datasets/inclusionAI/Ring-lite-rl-data.Ring-lite-distill-preview-sft-data
🤖 ModelScope
🤗 HuggingFace
🖥️ GitHub
Ring-lite-distill-preview
The Ring-lite-distill-preview Dataset comprises the following components:
Ring-lite-distill-preview-sft-data: A subset of SFT data used for training Ring-lite-distill-preview.
Ring-lite-distill-preview-dpo-data: A subset of DPO data used for training Ring-lite-distill-preview.
Ring-lite-distill-preview-sft-data
This is a subset of the SFT data used during the… See the full description on the dataset page: https://huggingface.co/datasets/inclusionAI/Ring-lite-distill-preview-sft-data.litex-math23k
Litex Math23K
This dataset contains 22,329 standalone Litex artifacts derived from Math23K
annotated equations. Each record stores a complete .lit file, its formal
goal, a proof-shape description, and a content hash.
The original Chinese questions and natural-language solutions are not included.
This is a formal-code corpus and verifier regression artifact, not a
redistribution of Math23K.
Verification boundary
Each artifact is a checkable calculation model. The… See the full description on the dataset page: https://huggingface.co/datasets/Sanyan/litex-math23k.lite_SFT_train_7lanlite_SFT_train_7lan
This dataset is designed for training and fine-tuning language models with multilingual question-answer pairs in seven languages: English (en), Arabic (ar), Urdu (ur), Persian/Farsi (fa), Indonesian (id), Turkish (tr), and Bengali (bn). The database contains over 1,300 high-quality Q&A entries, each fully translated across all seven languages. Each entry includes:
Original question-answer pairs in English
Translated versions for Arabic, Urdu, Persian, Indonesian, Turkish… See the full description on the dataset page: https://huggingface.co/datasets/mazrba/lite_SFT_train_7lan.lemonseed-uni-literature
lemonseed-uni-literature
LemonSeed — literature prose (book reviews & literary text).
Format
JSON Lines (.jsonl), one example per line.
Provenance & License
Literary prose/reviews. Provenance spans Project Gutenberg (public domain) and web-sourced book-review text; marked 'other' pending a definitive source audit.
literary-genre-examples
Literary Genre Dataset
This dataset contains a curated list of 86 fiction and nonfiction genres, each accompanied by a representative example paragraph. The example texts illustrate the typical tone, writing style, and content characteristics for each genre.
Genres Covered: 86 total, spanning popular and niche categories in both fiction and nonfiction.
Genre Types: Marked as either Fiction or Nonfiction.
Example Paragraphs: Each genre includes a sample paragraph written to capture… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/literary-genre-examples.solveall-literature-priors
SolveAll Literature-Grounded Priors
Dataset summary
SolveAll Literature-Grounded Priors is an English-language dataset of
open-ended mathematical and scientific research problems paired with realistic
user priors whose epistemic relationship to the literature is explicitly
annotated. Each claim-bearing example is connected to one or more short
passages from identified literature sources. The passages are used to classify
the user's prior as contradicted, supported… See the full description on the dataset page: https://huggingface.co/datasets/PranathReddy/solveall-literature-priors.hermes-agent-NoCOT
🧠 Hermes Agent No‑COT – Cleaned Function‑Calling Traces
Hermes Agent No‑COT is a curated, instruction‑style dataset derived from the lambda/hermes-agent-reasoning-traces (GLM‑5.1 split).It contains 7,055 multi‑turn tool‑calling conversations that have been cleaned and restructured for supervised fine‑tuning of small, efficient agentic models – especially those that use function‑calling within a chat environment.
✅ Why "No‑COT"?Every chain‑of‑thought (<think>…</think>) block has… See the full description on the dataset page: https://huggingface.co/datasets/LiteMind/hermes-agent-NoCOT.literary-dataset-pack
Literary Dataset Pack
A rich and diverse multi-task instruction dataset generated from classic public domain literature.
📖 Overview
Literary Dataset Pack is a high-quality instruction-tuning dataset crafted from classic literary texts in the public domain (e.g., Alice in Wonderland). Each paragraph is transformed into multiple supervised tasks designed to train or fine-tune large language models (LLMs) across a wide range of natural language understanding and generation… See the full description on the dataset page: https://huggingface.co/datasets/codeXpedite/literary-dataset-pack.Huatuo26M-Lite
Huatuo26M-Lite 📚
Table of Contents 🗂
Dataset Description 📝
Dataset Information ℹ️
Data Distribution 📊
Usage 🔧
Citation 📖
Dataset Description 📝
Huatuo26M-Lite is a refined and optimized dataset based on the Huatuo26M dataset, which has undergone multiple purification processes and rewrites. It has more data dimensions and higher data quality. We welcome you to try using it.
Dataset Information ℹ️
Dataset Name:… See the full description on the dataset page: https://huggingface.co/datasets/dihdaidh/Huatuo26M-Lite.literary-synthesis
Literary Synthesis
This dataset repurposes the original agentlans/literary-reasoning
data by reformatting it as creative writing prompts paired with literary-style outputs.
Writing style attributes were put in random order, with prompts randomly either prepended or appended.
The output text has been cleaned to make it suitable for creative writing and literary generation tasks.
The rows were sorted by increasing reading difficulty for curriculum learning.
drosophila-literature-corpus
Drosophila Literature Corpus
A corpus of full-text scientific articles from PubMed Central related to Drosophila melanogaster gene research.
Dataset Description
This corpus contains ~17,000 full-text scientific articles downloaded from the PubMed Central Open Access Subset via the BioC-PMC API. The articles are associated with genes that have expert-curated summaries in FlyBase.
Usage
from datasets import load_dataset
corpus =… See the full description on the dataset page: https://huggingface.co/datasets/jimmyzxj/drosophila-literature-corpus.AutoMoT-PDM-Lite-BEV-Encoder-Indexes
AutoMoT PDM-Lite BEV Encoder Indexes
This dataset provides the prepared PDM-Lite JSONL indexes for AutoMoT training.
Files
pdm_lite_2hz_2tp_train_bev_encoder.jsonl
pdm_lite_2hz_2tp_val_bev_encoder.jsonl
Each row contains four historical front-camera paths in image, the current
front-camera path in front, trajectory and route supervision, future-speed
supervision, and a reference to the precomputed current-frame BEV feature:
bev_encoder_feature… See the full description on the dataset page: https://huggingface.co/datasets/HqH1111/AutoMoT-PDM-Lite-BEV-Encoder-Indexes.Lite-Thinking
Lite-Thinking: A Large-Scale Math Dataset with Moderate Reasoning Steps
Motivation
With the rapid popularization of large reasoning models, like GPT-4o, Deepseek-R1, and Qwen3, there are increasing researchers seeking to build their own reasoning models.
Typically, small foundation models are chosen; following the mature technology of Deepseek-R1, mathematical datasets are mainly adopted to build training corpora.
Despite existing available datasets, represented by… See the full description on the dataset page: https://huggingface.co/datasets/Jax-dan/Lite-Thinking.Hermes-Coworker-Flash
⚡ Hermes Coworker Flash – Fast, No‑Code Agent Conversations
Hermes Coworker Flash is a curated instruction‑style dataset built from the best “everyday assistant” traces of lambda/hermes-agent-reasoning-traces.It combines GLM‑5.1 and kimi-2.5 splits, keeping only the non‑programming, quick‑turnaround co‑worker tasks — the ones a user would ask a fast AI assistant, not a full‑fledged software engineer.
🧹 All chain‑of‑thought (<think>…</think>) has been removed so the model learns to… See the full description on the dataset page: https://huggingface.co/datasets/LiteMind/Hermes-Coworker-Flash.Sera-4.6-Lite-T2-v4-1000
laion/Sera-4.6-Lite-T2-v4-1000
Row-subset of allenai/Sera-4.6-Lite-T2
(the dataset upstream SERA-8B was trained on), with OpenAI tool_calls pre-rendered
into the content string as Hermes/Qwen3-style <tool_call>...</tool_call> wire tokens
and tool responses wrapped as <tool_response>...</tool_response>.
This mirrors Ai2's sera/datagen/data/postprocess/utils.py::transform_traj_hermes
(default tool_call_format: "hermes") which is the missing step between the public
Sera-4.6-Lite-T2… See the full description on the dataset page: https://huggingface.co/datasets/laion/Sera-4.6-Lite-T2-v4-1000.Ring-lite-distill-preview-dpo-data
🤖 ModelScope
🤗 HuggingFace
🖥️ GitHub
Ring-lite-distill-preview
The Ring-lite-distill-preview Dataset comprises the following components:
Ring-lite-distill-preview-sft-data: A subset of SFT data used for training Ring-lite-distill-preview.
Ring-lite-distill-preview-dpo-data: A subset of DPO data used for training Ring-lite-distill-preview.
Ring-lite-distill-preview-dpo-data
This is a subset of DPO data used to train the… See the full description on the dataset page: https://huggingface.co/datasets/inclusionAI/Ring-lite-distill-preview-dpo-data.Simple-agent-traces
📱 Simple Agent Traces – Tiny Tool‑Calling Conversations for Small Models
Simple Agent Traces is a compact, hand‑picked dataset of 605 real‑world tool‑calling conversations, each carefully truncated to ≤8,192 tokens (using the SmolLM2‑360M tokenizer).It is purpose‑built for training and fine‑tuning tiny language models (≤500M) that must run on‑device – smartphones, edge devices, or any environment with strict memory and latency constraints.
🧹 No chain‑of‑thought, no fluff.Every… See the full description on the dataset page: https://huggingface.co/datasets/LiteMind/Simple-agent-traces.textbooks-lite-700k-sharegpt-enPurified-openai-messages
📖 textbooks-lite-700k-enPurified-openai-messages
textbooks-lite-700k-enPurified is a highly curated, "prose-first" subset of the original jtatman/textbooks-lite-700k-sharegpt.
The enPurified collection is built on a specific philosophy: Specialization through Purity. While the ecosystem is rich with datasets for competitive programming and complex mathematics, high-quality, fluent English prose is often diluted by technical syntax or symbolic logic.
For this dataset, the enPurified… See the full description on the dataset page: https://huggingface.co/datasets/enPurified/textbooks-lite-700k-sharegpt-enPurified-openai-messages.DeepThink-Code-Lite
🧠 DeepThink Code - Lite Version (Reasoning & Code)
⚠️ Note : Ceci est la version LITE (645 exemples) destinée à l'évaluation et à la recherche non-commerciale.
🚀 Pour la version complète (20k+ exemples) avec Licence Commerciale, Cliquez ici pour accéder à l'offre complète sur Gumroad
Description
Ce dataset est conçu pour entraîner des modèles de langage à raisonner avant de coder. Contrairement aux datasets classiques qui donnent juste la solution, celui-ci force… See the full description on the dataset page: https://huggingface.co/datasets/Jessylg27/DeepThink-Code-Lite.Huatuo26M-Lite
Huatuo26M-Lite 📚
Table of Contents 🗂
Dataset Description 📝
Dataset Information ℹ️
Data Distribution 📊
Usage 🔧
Citation 📖
Dataset Description 📝
Huatuo26M-Lite is a refined and optimized dataset based on the Huatuo26M dataset, which has undergone multiple purification processes and rewrites. It has more data dimensions and higher data quality. We welcome you to try using it.
Dataset Information ℹ️
Dataset Name:… See the full description on the dataset page: https://huggingface.co/datasets/mingys/Huatuo26M-Lite.