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README.md
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tags:
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- robotics
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- community
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- so100
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- manipulation
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- smolvla
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A large-scale community-contributed robotics dataset for vision-language-action learning, featuring **340 datasets** from **117 contributors** worldwide.
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This dataset represents the second major release of community-contributed robotics data, expanding upon the
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## π Overview
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## π Usage
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**1. Install LeRobot**
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Follow the [official LeRobot installation guide](https://huggingface.co/docs/lerobot/installation):
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```bash
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# Create conda environment with Python 3.10
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conda create -y -n lerobot python=3.10
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conda activate lerobot
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# Install ffmpeg (required for video processing)
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conda install ffmpeg -c conda-forge
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git clone https://github.com/huggingface/lerobot.git
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cd lerobot
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# Install LeRobot from Source
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pip install -e .
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```
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**2. Authenticate with Hugging Face**
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You need to be logged in to access the dataset:
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### Download the Dataset
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```python
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dataset_path = snapshot_download(
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repo_id="HuggingFaceVLA/community_dataset_v2",
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repo_type="dataset",
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local_dir="./community_dataset_v2"
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)
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```
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### Load Individual Datasets
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import os
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# Browse available datasets
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for contributor in os.listdir("./
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contributor_path = f"./
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if os.path.isdir(contributor_path):
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for dataset in os.listdir(contributor_path):
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print(f"π {contributor}/{dataset}")
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# Load a specific dataset (requires authentication)
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dataset = LeRobotDataset(
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repo_id="local",
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root="./
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)
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# Access episodes and observations
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print(f"Total frames: {len(dataset)}")
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```
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### Integration with SmolVLA
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```python
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COMING SOON
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# This dataset is designed for training VLA models
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# Compatible with SmolVLA training pipelines
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# needs testing
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```
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## π§ Dataset Format
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Each dataset contains:
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- **Multi-task policy development**
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- **Embodied AI research**
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## π Revisions
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- **v2.0**: Expanded community collection
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- 340 datasets from 117 contributors
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- Standardized LeRobot v2.0/v2.1 format
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- Advanced quality filtering and validation
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- Comprehensive automated processing pipeline
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## π€ Community Contributions
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This dataset exists thanks to the generous contributions from researchers, hobbyists, and institutions worldwide. Each dataset represents hours of careful data collection and curation.
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Check the [blogpost](https://huggingface.co/blog/lerobot-datasets) for more information
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## π License
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Released under Apache 2.0 license. Individual datasets may have additional attribution requirements - please check contributor documentation.
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## π Related Work
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- [
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- [SmolVLA model](https://huggingface.co/lerobot/smolvla_base)
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- [SmolVLA Blogpost](https://huggingface.co/blog/smolvla)
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- [SmolVLA Paper](https://huggingface.co/papers/2506.01844)
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tags:
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- robotics
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- community
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- vlab
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- so100
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- manipulation
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- smolvla
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A large-scale community-contributed robotics dataset for vision-language-action learning, featuring **340 datasets** from **117 contributors** worldwide.
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This dataset represents the second major release of community-contributed robotics data, expanding upon the [Community Dataset v1](https://huggingface.co/datasets/HuggingFaceVLA/community_dataset_v1).
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## π Overview
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## π Usage
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**1. Authenticate with Hugging Face**
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You need to be logged in to access the dataset:
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### Download the Dataset
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```python
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hf download HuggingFaceVLA/community_dataset_v1 \
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--repo-type=dataset \
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--local-dir /path/local_dir/community_dataset_v1
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```
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### Load Individual Datasets
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import os
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# Browse available datasets
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for contributor in os.listdir("./community_dataset_v1"):
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contributor_path = f"./community_dataset_v1/{contributor}"
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if os.path.isdir(contributor_path):
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for dataset in os.listdir(contributor_path):
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print(f"π {contributor}/{dataset}")
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# Load a specific dataset (requires authentication)
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dataset = LeRobotDataset(
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repo_id="local",
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root="./community_dataset_v1/contributor_name/dataset_name"
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)
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# Access episodes and observations
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print(f"Total frames: {len(dataset)}")
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```
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## π§ Dataset Format
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Each dataset contains:
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- **Multi-task policy development**
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- **Embodied AI research**
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## π€ Community Contributions
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This dataset exists thanks to the generous contributions from researchers, hobbyists, and institutions worldwide. Each dataset represents hours of careful data collection and curation.
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Check the [blogpost](https://huggingface.co/blog/lerobot-datasets) for more information
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## π Related Work
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- [VLAb Framework](https://github.com/huggingface/VLAb)
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- [SmolVLA model](https://huggingface.co/lerobot/smolvla_base)
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- [SmolVLA Blogpost](https://huggingface.co/blog/smolvla)
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- [SmolVLA Paper](https://huggingface.co/papers/2506.01844)
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