datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
BetterDataset-12M
Dataset
Mixed pretraining dataset built from:
Source
Config
Weight
HuggingFaceTB/smollm-corpus
fineweb-edu-dedup
20%
openbmb/Ultra-FineWeb-L3
Ultra-FineWeb-L3-en-Multi-Style-Synthetic
10%
HuggingFaceTB/dclm-edu
—
20%
HuggingFaceFW/finewiki
en
20%
HuggingFaceTB/cosmopedia
stories
2%
HuggingFaceTB/cosmopedia
stanford
2%
HuggingFaceFW/finephrase
all
6%
HuggingFaceTB/finemath
finemath-l4
5%
nampdn-ai/tiny-math-textbooks
—
5%
HuggingFaceTB/cosmopedia… See the full description on the dataset page: https://huggingface.co/datasets/GODELEV/BetterDataset-12M.godot-gdscript-dataset
Godot GDscript Code Dataset
This dataset contains GDScript code from 5k+ github repositories. Data from each repo has been extracted into a text file. Each text file contains the code from all .gd files & README.md text (if the README was not empty in the original repo).
Original forum post:
https://diffused.to/Thread-Godot-GDscript-Code-Dataset-5k
Dataset collection date
June 2025
Dataset structure:
📂 files/
├── repo-name-1.txt
├── repo-name-2.txt… See the full description on the dataset page: https://huggingface.co/datasets/wallstoneai/godot-gdscript-dataset.godot-gdscript-dataset
Godot GDscript Code Dataset
This dataset contains GDScript code from 5k+ github repositories. Data from each repo has been extracted into a text file. Each text file contains the code from all .gd files & README.md text (if the README was not empty in the original repo).
Original forum post:
https://diffused.to/Thread-Godot-GDscript-Code-Dataset-5k
Dataset collection date
June 2025
Dataset structure:
📂 files/
├── repo-name-1.txt
├──… See the full description on the dataset page: https://huggingface.co/datasets/icici121/godot-gdscript-dataset.taskweft-fbd-godot-train
taskweft-fbd-godot-train
Intents and the IEC 61131-3 Function Block Diagrams that carry them out, as an
EditScore-shaped corpus: one root row per intent, three candidates per row (rank1 the
reference diagram, rank3 one that compiles and does the wrong thing, rank5 one the
compiler refuses), and one score row per candidate from the engine itself: api_runner.gd performed the calls on the fixture scene and the returns were read back. Every row is
constructed from a template and a… See the full description on the dataset page: https://huggingface.co/datasets/chibifire/taskweft-fbd-godot-train.storyweaver-writing-zh
StoryWeaver 中文写作质量评测集
12 道按写作失效模式反推设计的中文创作题、4 个参赛者写出的 48 篇章节、432 条逐维度两两判决（含裁判完整推理原文）。
来自 StoryWeaver 的写作质量评测轨道。榜单：https://storyweaver.cn/benchmark-writing.html
核心结论
接系统比换一代底模更管用。同一底模接上多 Agent 系统后的胜率：k2.5 **75.1%**、k2.6 **60.2%**；而 k2.5(系统) 对 k2.6(裸) 是 70.3%，反过来只有 37.2%——系统加持能把旧一代底模抬过裸的新一代底模。系统档拿下 22 个维度里的 20 个榜首，包括全部 9 个负向维度。
k2.5 与 k2.6 之间 54.7%，落在噪音带内，不构成结论。
题目怎么设计的
每道题咬住 rubric 里的一个维度或负向维度，用硬约束逼出功力：… See the full description on the dataset page: https://huggingface.co/datasets/godwei123/storyweaver-writing-zh.ChatGPT-Jailbreak-Prompts-rubend18
Dataset Card for Dataset Name
Name
ChatGPT Jailbreak Prompts
Dataset Summary
ChatGPT Jailbreak Prompts is a complete collection of jailbreak related prompts for ChatGPT. This dataset is intended to provide a valuable resource for understanding and generating text in the context of jailbreaking in ChatGPT.
Languages
[English]
Python_GOD_Coder_Omniforge_AI_12k
Python GOD Coder Omniforge AI 12k
Creator: Within Us AI
A 12,000-row mixed-format Python coding dataset designed as a sharpening corpus for building a small but dangerous Python specialist.
This dataset is intentionally focused on the practical behaviors that matter for a modern Python coding model:
implementation with tests
strict code-only instruction following
debugging and repair
refactoring for readability and production readiness
next-token code completion… See the full description on the dataset page: https://huggingface.co/datasets/WithinUsAI/Python_GOD_Coder_Omniforge_AI_12k.godot-lora-dataset
Godot LORA Dataset
GDScript training dataset for fine-tuning code models on Godot engine development.
Dataset Info
Total samples: 476
Train split: 428
Validation split: 48
Format: JSONL (instruction, input, output)
Language: GDScript (Godot 4.x)
Languages: German instructions, GDScript code
Sources
godotengine/godot-demo-projects
GDQuest/godot-open-rpg
GDQuest/godot-3d-dodge-the-creeps
bitbrain/beehave (behavior trees)
limboai/limboai (AI for Godot)… See the full description on the dataset page: https://huggingface.co/datasets/matzejo/godot-lora-dataset.storyweaver-chunking-zh
StoryWeaver 中文叙事切分语料
12 篇中文叙事短文，按切分算法的失效模式反推设计，用于比较 chunking 策略在长篇小说创作场景下的表现。
来自 StoryWeaver 的切分质量评测轨道。榜单：https://storyweaver.cn/benchmark-chunking.html
这批语料的特别之处
它不是真实小说的随机采样，而是每篇专门写来触发某一类切分失效：
对话密集、闪回嵌套、隐晦转场、双线交替、同场景多视角、同场景话题漂移……
这么设计是为了让不同算法拉开差距——真实文本里这些情况稀疏出现，抽样评测容易得到"各方法差不多"的钝化结论。代价是分布有偏，解读结果时必须计入这一点。
文件
corpus.jsonl（12 行）
字段
说明
doc_id
篇名（中文，如 夜班、面馆）
text
全文
chars
字数
leaderboard.json
首轮评测的汇总结果：6… See the full description on the dataset page: https://huggingface.co/datasets/godwei123/storyweaver-chunking-zh.NuminaMath-CoT
Dataset Card for NuminaMath CoT
Dataset Summary
Approximately 860k math problems, where each solution is formatted in a Chain of Thought (CoT) manner. The sources of the dataset range from Chinese high school math exercises to US and international mathematics olympiad competition problems. The data were primarily collected from online exam paper PDFs and mathematics discussion forums. The processing steps include (a) OCR from the original PDFs, (b) segmentation into… See the full description on the dataset page: https://huggingface.co/datasets/godmodes/NuminaMath-CoT.Kishor_V2_53K_LLM_Prompt-Response_Pairs
Kishor V2: 53K Prompt-Response Dataset
Kishor V2 is a diverse and compact dataset curated for training small to medium-sized language models. It includes 53,000 structured prompt-response pairs across multiple domains to simulate human-like dialogue, reasoning, and general intelligence.
📦 File
KishorV2_dataset.jsonl: Main dataset in JSON Lines format.
📂 Format
Each line is a JSON object with:
{
"type": "qa" | "dialogue" | "quote" | "fact" | "reasoning" |… See the full description on the dataset page: https://huggingface.co/datasets/GODELEV/Kishor_V2_53K_LLM_Prompt-Response_Pairs.chat_his