datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
koch_tutorialThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.0",
"robot_type": "koch",
"total_episodes": 50,
"total_frames": 21267,
"total_tasks": 1,
"total_videos": 100,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:50"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/aliberts/koch_tutorial.ccai-nlp-tutorial-1deception-probing-tutorial
Deception probing tutorial — Gemma-2-9B-IT activations
Precomputed residual-stream activations for a hands-on replication of
Natarajan et al. (2026), One Probe Won't Catch Them All (arXiv:2602.01425),
which builds on Goldowsky-Dill et al. (2025), Detecting Strategic Deception with
Linear Probes.
The point of shipping activations rather than a model: everything scientifically
interesting in both papers happens downstream of the forward pass. With these
vectors the whole tutorial… See the full description on the dataset page: https://huggingface.co/datasets/Rutabin/deception-probing-tutorial.easytranscriber_tutorialstutorials_summary
Tutorials Summary Text Dataset
This is the summary text dataset of sysmlv2's official tutorials pdf. With the text explanation and code examples in each page, organized in both Chinese and English natural language text. Useful for training LLM and teach it the basic knowledge and conceptions of sysmlv2.
182 records in total.
English Full Summary
page_1-41.md
page_42-81.md
page_82-121.md
page_122-161.md
page_162-183.md
中文完整版
page_1-41.md
page_42-81.md
page_82-121.md… See the full description on the dataset page: https://huggingface.co/datasets/sysmlv2research/tutorials_summary.tutorial_v2This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "omy",
"total_episodes": 50,
"total_frames": 9758,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 20,
"splits": {
"train": "0:50"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/y0-0n/tutorial_v2.MFA_tutorial_2025-04-28_PAPPSThis repo contains the material for this Montreal Forced Aligner Tutorial.
The recordings are from ALLSTAR and Mozilla Common Voice.
tutorial_v2This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "omy",
"total_episodes": 50,
"total_frames": 9758,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 20,
"splits": {
"train": "0:50"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/Jeongeun/tutorial_v2.transformer-from-scratch-tutorial
Implementing Transformer from Scratch: A Step-by-Step Guide
This repository provides a detailed guide and implementation of the Transformer architecture from the "Attention Is All You Need" paper. The implementation focuses on understanding each component through clear code, comprehensive testing, and visual aids.
For implementions of more recent architectural innovations from DeepSeek, see the Related Implementations section.
Quick Start
View the complete… See the full description on the dataset page: https://huggingface.co/datasets/bird-of-paradise/transformer-from-scratch-tutorial.multi_dimensional_features_tutorialmuon-tutorial
Understanding the Muon Optimizer: Theory and Implementation
📘 Contents
Try It Yourself -- base and advanced implementions
Introduction to Muon
The Problem: Skewed Singular Values
Newton-Schulz Orthogonalization
Muon vs. AdamW
When to Use Muon
Implementation Details
Practical Performance Analysis
Optimization Techniques
Lessons Learned
Concludsion
Extended Work
🧪 Try It Yourself
The included Colab notebook allows you to run all experiments and implement Muon… See the full description on the dataset page: https://huggingface.co/datasets/bird-of-paradise/muon-tutorial.spacr-tutorials
spaCR tutorial media
Narration and 4K video for the spaCR
interactive tutorial library, served directly to
https://einarolafsson.github.io/spacr/tutorials/.
spaCR is a toolkit for microscopy and single-cell analysis of pooled CRISPR
screens. This repository holds the media its 40-lesson tutorial player streams;
it is not a training dataset.
Why it lives here
GitHub Pages caps a published site at 1 GB. The full narration set is 2,662 MiB
across 54 voices, so the… See the full description on the dataset page: https://huggingface.co/datasets/einarolafsson/spacr-tutorials.tutorialcode_tutorials
Coding Tutorials
This comprehensive dataset consists of 500,000 documents, summing up to around 1.5 billion tokens.
Predominantly composed of coding tutorials, it has been meticulously compiled from various web crawl datasets like RefinedWeb, OSCAR, and Escorpius.
The selection process involved a stringent filtering of files using regular expressions to ensure the inclusion of content that contains programming code (most of them).
These tutorials offer more than mere code snippets.… See the full description on the dataset page: https://huggingface.co/datasets/mponty/code_tutorials.deception-probing-tutorial-lite
Deception probing tutorial — Gemma-2-9B-IT activations (lite)
Precomputed residual-stream activations for a hands-on replication of
Natarajan et al. (2026), One Probe Won't Catch Them All (arXiv:2602.01425),
which builds on Goldowsky-Dill et al. (2025), Detecting Strategic Deception with
Linear Probes.
The point of shipping activations rather than a model: everything scientifically
interesting in both papers happens downstream of the forward pass. With these
vectors the whole… See the full description on the dataset page: https://huggingface.co/datasets/Rutabin/deception-probing-tutorial-lite.tutorialstutorial-ball-2
tutorial-ball-2 (LeRobot) — TsFile
This dataset is a lossless conversion to the Apache TsFile
format of the HuggingFace LeRobot dataset
notmahi/tutorial-ball-2:
a low-dimensional robot tutorial trajectory dataset (no video).
Original dataset
Source dataset: notmahi/tutorial-ball-2
Format: early LeRobot format (meta_data/ + safetensors)
Content: purely numeric low-dimensional state/action trajectories —
314,074 frames / 751 episodes / 30 fps. No images or video… See the full description on the dataset page: https://huggingface.co/datasets/THULab/tutorial-ball-2.code-tutorials-en
Dataset Card for "code-tutorials-en"
en only
100 words or more
reading ease of 50 or more
DatasetDict({
train: Dataset({
features: ['text', 'url', 'dump', 'source', 'word_count', 'flesch_reading_ease'],
num_rows: 223162
})
validation: Dataset({
features: ['text', 'url', 'dump', 'source', 'word_count', 'flesch_reading_ease'],
num_rows: 5873
})
test: Dataset({
features: ['text', 'url', 'dump', 'source', 'word_count'… See the full description on the dataset page: https://huggingface.co/datasets/BEE-spoke-data/code-tutorials-en.so101-tutorial-eraser-32This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "so101_follower",
"total_episodes": 38,
"total_frames": 22664,
"total_tasks": 1,
"total_videos": 76,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:38"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/masakinoda/so101-tutorial-eraser-32.rustAI_tutorial_datasetosworld-tutorial-ragfiltered-finephrase-tutorialbut-they-are-cats-tutorial
Dataset Card for But They Are Cats Tutorials
This dataset is presented and used in Level Up Your Tutorials: VLMs for Game Tutorials Quality Assessment.
Dataset Details
The dataset is designed for Visual Question answering. It is composed of game screenshots, questions, and answers.
The questions and the answers are direct to provide a more effective evaluation independent of the syntax.
Question: "Do distractions affect the cats in the same way?" Answer: "The… See the full description on the dataset page: https://huggingface.co/datasets/DarthReca/but-they-are-cats-tutorial.tutorial-senegal-lclucrag-tutorial-prebuilt-indexes
🔍 Pre-built Indexes for RAG Tutorial
Welcome to the official repository for Pre-built Dense Indexes used in our RAG (Retrieval-Augmented Generation) Tutorial.
This repository is designed to help learners, instructors, and researchers easily integrate domain-specific dense retrieval into their RAG workflows without spending time building indexes from scratch.
📦 What This Repository Contains
This repository hosts ready-to-use FAISS-based dense indexes and supporting… See the full description on the dataset page: https://huggingface.co/datasets/ShubhamC/rag-tutorial-prebuilt-indexes.20250524_buildwithai_tutorial_280pxmedical-cases-classification-tutorial
About
This is a pre-filtered and pre-split dataset for the HPE Generative AI "Medical Transcript Classification" tutorials.
No-Code Version (UI Only)
Notebooks Version
tutorial_vla_datasetThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "omy",
"total_episodes": 50,
"total_frames": 9758,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 20,
"splits": {
"train": "0:50"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/csharon/tutorial_vla_dataset.tutorial-imagestutorial-ball