datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
classify-blocks-512-local
classify-blocks 512
A LeRobot v3.0 dataset for one long-horizon pick-and-place task: a block is picked from a compartment of a
transparent organiser, carried to the matching compartment that shows the same block class, and released.
The snapshot holds 512 episodes / 201,004 frames at 15 fps and 640x480 RGB from a wrist-mounted camera.
Robot type is so_follower; the six action and state channels are shoulder_pan, shoulder_lift,
elbow_flex, wrist_flex, wrist_roll (degrees) and… See the full description on the dataset page: https://huggingface.co/datasets/rubatotree/classify-blocks-512-local.dwd-hf-classify-1
DWD HF CLASSIFY 1
Dataset gathered from a 20m anntena from slovakia, recieving dwd (militarry weather info)
Curently super small, recieving tooks a lot of time at 50 baud (50bps)
It was made by using a known list of types and qualities and training a small ml to help together with some rules hardcoded to classify the type and quality.
If there are issues please report them and i will try improoving the ml and rules.
TYPE
= garbage / broken line
= metadata… See the full description on the dataset page: https://huggingface.co/datasets/simonko912/dwd-hf-classify-1.test-classify-5epThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "agilex_piper_bimanual",
"total_episodes": 5,
"total_frames": 1050,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 20,
"splits": {
"train": "0:5"
},
"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/PranayTest/test-classify-5ep.lerobot-tomato-classify-2This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 40,
"total_frames": 8022,
"total_tasks": 2,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:40"
},
"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/taetae77/lerobot-tomato-classify-2.asia-owid-icd-code-version-used-to-classify-causes-of-death
Icd Code Version Used To Classify Causes Of Death | Asia (Our World in Data)
🌏 1,036 observations · 37 Asia countries · 1950–2023 · Repackaged by Electric Sheep Asia
TL;DR
This dataset contains 1,036 observations of Icd Code Version Used To Classify Causes Of Death data across 37 Asia countries, spanning 1950–2023.
About the source
Source: Our World in Data
Publisher: Our World in Data
License: cc-by-4.0
Topic: Icd Code Version Used To… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-owid-icd-code-version-used-to-classify-causes-of-death.classify1This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "omx_follower",
"total_episodes": 801,
"total_frames": 328724,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:801"
},
"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/angrynose/classify1.lerobot-tomato-classifyThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 100,
"total_frames": 21711,
"total_tasks": 2,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:100"
},
"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/taetae77/lerobot-tomato-classify.Puntuation_mark_classifyrecord-classify_fixed_2record-classify_fixed_1wildchat-factual-classifyrecord-classify_1emb_classifyemb_classify_captionafrica-owid-icd-code-version-used-to-classify-causes-of-death
Icd Code Version Used To Classify Causes Of Death | Africa (Our World in Data) | Africa (Electric Sheep Africa metadata inventory)
Size category: n<1K - Formats: parquet - Sector: other_unclassified - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-owid-icd-code-version-used-to-classify-causes-of-death.wildchat-factual-classify-wiiretrievalemb_classify_filtered_4shotrecord-classify_5emb_classify_single_user_captionrecord-classify_fixed_3toxic-classifyeurope-owid-icd-code-version-used-to-classify-causes-of-death
Icd Code Version Used To Classify Causes Of Death | Europe (Our World in Data)
🇪🇺 2,102 observations · 42 Europe countries · 1950–2023 · Repackaged by Electric Sheep Europe
TL;DR
This dataset contains 2,102 observations of Icd Code Version Used To Classify Causes Of Death data across 42 Europe countries, spanning 1950–2023.
About the source
Source: Our World in Data
Publisher: Our World in Data
License: cc-by-4.0
Topic: Icd Code Version Used… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepeurope/europe-owid-icd-code-version-used-to-classify-causes-of-death.autotrain-data-classifyerrecord-classify_fixed_0record-classify_fixed_4classifying_member_activity_levels_distilbert_dataset
Classifying Member Activity Levels
Description: Categorize members based on their activity levels, such as low, medium, and high, to enable tailored engagement and retention strategies.
How to Use
Here is how to use this model to classify text into different categories:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model_name = "interneuronai/classifying_member_activity_levels_distilbert"
model =… See the full description on the dataset page: https://huggingface.co/datasets/interneuronai/classifying_member_activity_levels_distilbert_dataset.wildentities_classify