tutorial
Gemma-2-27B-Technical-Tutorial-Summarization-QLoRA-i1-GGUFndebuhr_-_Mistral-7B-Technical-Tutorial-Summarization-QLoRA-ggufGemma-2-27B-Technical-Tutorial-Summarization-QLoRA-GGUFdiegollg_-_FineLlama-3.1-8B-tutorial-ggufminecraft-ai-training-tutorialddpm-floorplans_tutorial-128ddpm-floorplans_tutorial-128ddpm-floorplans_tutorial-128_bw
Datasets
All datasets matching “tutorial”robot-learning-tutorial-dataThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101_follower",
"total_episodes": 1,
"total_frames": 1776,
"total_tasks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:1"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4"… See the full description on the dataset page: https://huggingface.co/datasets/omkarmayekar555/robot-learning-tutorial-data.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.easytranscriber_tutorialskoch_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.deception-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.ccai-nlp-tutorial-1