datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SimpleStories
📘📕 SimpleStories 📙📗
SimpleStories is a dataset of >2 million model-generated short stories. It was made to train small, interpretable language models on it. The generation process is open-source: To see how the dataset was generated, or to generate some stories yourself, head over to this repository.
If you'd like to commission other languages or story formats, feel free to send mail.
When using SimpleStories in your work, please cite the SimpleStories paper:… See the full description on the dataset page: https://huggingface.co/datasets/SimpleStories/SimpleStories.multilingual-textarena-SimpleTak-v0-train-v2
TextArena Language Trajectories
This dataset contains language-conditioned TextArena trajectory data.
Each dataset configuration corresponds to a different model, experiment group, or source folder.
Available configurations:
gemma4-e4b-it
qwen3-4b
ministral3-3b-instruct
Usage
Install the datasets library:
pip install datasets
Load a specific configuration:
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/The-CoLab/multilingual-textarena-SimpleTak-v0-train-v2.SimpleStories-JA
📘📕 SimpleStories 📙📗
このデータセットは、gpt-4o-miniによって生成された短編小説で出来ているデータセットです。生成方法や、自分で物語を生成する方法については、こちらのリポジトリをご覧ください。
他の言語や物語形式の制作を希望される場合は、メールにてお問い合わせください。
SimpleStoriesは、EldenとLiによるTinyStoriesの改良版です。
特徴
物語の注釈情報（theme、topic、styleなど）
多様性の高さ
2024年のモデルによって生成
NLPのデータが用意しているためフィルタリングしやすい
以下の言語版が利用可能：
英語
日本語
他にも追加予定
This dataset is a collection of short stories generated by gpt-4o-mini (+ other models, soon). To see how this dataset was generated, or to generate some stories… See the full description on the dataset page: https://huggingface.co/datasets/SimpleStories/SimpleStories-JA.multilingual-textarena-SimpleTak-v0-train
TextArena Language Trajectories
This dataset contains language-conditioned TextArena trajectory data.
Each dataset configuration corresponds to a different model, experiment group, or source folder.
Available configurations:
gemma4-e4b-it
qwen3-4b
ministral3-3b-instruct
Usage
Install the datasets library:
pip install datasets
Load a specific configuration:
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/The-CoLab/multilingual-textarena-SimpleTak-v0-train.SimpleStories
📘📕 SimpleStories 📙📗
SimpleStories is a dataset of >2 million model-generated short stories. It was made to train small, interpretable language models on it. The generation process is open-source: To see how the dataset was generated, or to generate some stories yourself, head over to this repository.
If you'd like to commission other languages or story formats, feel free to send mail.
When using SimpleStories in your work, please cite the SimpleStories paper:… See the full description on the dataset page: https://huggingface.co/datasets/duoduoyeah/SimpleStories.ORCHESTRA-simple-1M
ORCHESTRA-simple-1M
GitHub: nk2028/ORCHESTRA-dataset
中文簡介
ORCHESTRA (cOmpRehensive Classical cHinESe poeTRy dAtaset) 是一個全面的古典中文詩歌的數據集，數據來自搜韻網。本數據集由 nk2028 進行格式轉換並發佈，希望透過公開高品質的古典中文詩歌數據，促進對古典中文詩歌及古典中文自然語言處理的研究。
ORCHESTRA-simple 是 ORCHESTRA 數據集的簡化格式，僅保留 id, title, group_index, type, dynasty, author, content 這 7 個欄位，而去除其他欄位，以簡化使用。
本資料集可用於大型語言模型的訓練。如欲作其他用途，請向數據提供者搜韻網諮詢。
English Introduction
ORCHESTRA (cOmpRehensive Classical cHinESe poeTRy dAtaset) is a comprehensive dataset of classical… See the full description on the dataset page: https://huggingface.co/datasets/Ayaka/ORCHESTRA-simple-1M.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.