generalist
RADAR-auxiliary-data
RADAR: Preprocessed Anatomical Masks for Merlin CT Data
This dataset provides preprocessed anatomical segmentation masks for the Merlin abdominal CT training set, generated by TotalSegmentator and post-processed for use with the RADAR framework. These masks enable anatomy-aware vision–language pretraining without any additional manual annotation.
Overview
RADAR is a generalist vision–language model trained on over 400,000 contrast-enhanced abdominal CT… See the full description on the dataset page: https://huggingface.co/datasets/radar-generalist/RADAR-auxiliary-data.real-generalistRubrics-generalist-judgments_gptmini-97.5-0.7-0.1-Qwen3-4B-64-2048-0.6Dataset for judgments_gptmini with Qwen3-4B on Rubrics-generalist with 2048 tokens and 0.6 temperature and 97.5 percentile and 0.7 absolute rubric satisfaction threshold and 0.1 minimum satisfaction delta
xlerobot_generalist_v2This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
18
],
"names": [
"left_arm_shoulder_pan.pos",
"left_arm_shoulder_lift.pos",
"left_arm_elbow_flex.pos",
"left_arm_wrist_flex.pos"… See the full description on the dataset page: https://huggingface.co/datasets/Odog16/xlerobot_generalist_v2.teach-generalist-v1
Canis.teach Generalist Dataset
Simple synthetic dataset for training Generalist tutoring models.
Project: Canis.teach - Learning that fits.
Subject: Generalist
Generated with: Canis.lab
Format: Simple ID:content pairs
Dataset Structure
{
"id": "unique_identifier",
"content": "tutoring conversation text"
}
This dataset contains educational conversations focused on Generalist topics, designed to teach effective tutoring behavior rather than just providing direct… See the full description on the dataset page: https://huggingface.co/datasets/CanisAI/teach-generalist-v1.Rubrics-generalist-judgments_gptmini-99-0.5-0.1-Qwen3-4B-64-2048-0.6Dataset for judgments_gptmini with Qwen3-4B on Rubrics-generalist with 2048 tokens and 0.6 temperature and 99 percentile and 0.5 absolute rubric satisfaction threshold and 0.1 minimum satisfaction delta