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README.md

@@ -7,122 +7,34 @@ tags:
 - manipulation
 - smolvla
 - lerobot
-- vision-language-action
-- embodied-ai
+- multi-user
+- collection
 task_categories:
 - robotics
 language:
 - en
 size_categories:
 - 100K<n<1M
-pretty_name: Community Dataset v1
 ---
 
 # Community Dataset v1
 
-A large-scale community-contributed robotics dataset for vision-language-action learning, featuring **128 datasets** from **55 contributors** worldwide.
+This is a large-scale community robotics dataset containing 128 individual datasets from multiple contributors.
 
-We used this dataset to pretrain SmolVLA [insert link to the model]. However, this is not a complete set, but the dataset that we selected using specific filters, like fps, min num of episodes, and some qualitative assessment of video qualities, using the https://huggingface.co/spaces/Beegbrain/FilterLeRobotData tool. We also manually curated the task descriptions for this subset of the dataset. 
+## Tags
 
-## 🌟 Overview
+- **smolvla**: Part of the SmolVLA project
+- **lerobot**: Compatible with LeRobot framework
+- **robotics**: Robotics manipulation tasks
+- **community**: Community-contributed datasets
+- **so100**: SO-100 related tasks
 
-This dataset represents a collaborative effort from the robotics and AI community to build comprehensive training data for embodied AI systems. Each contribution contains demonstrations of robotic manipulation tasks with the SO100 arm, recorded using [LeRobot tools](https://github.com/huggingface/lerobot), primarily focused on tabletop scenarios and everyday object interactions.
-
-## 📊 Dataset Statistics
-
-| Metric | Value |
-|--------|-------|
-| **Total Datasets** | 128 |
-| **Total Episodes** | 11,132 |
-| **Total Frames** | 5,105,808 |
-| **Total Videos** | 22,065 |
-| **Contributors** | 55 |
-| **Weighted Average FPS** | 30.4 |
-| **Average Episodes per Dataset** | 87.0 |
-| **Total Duration** | 46.9 hours |
-| **Average Hours per Dataset** | 0.37 |
-| **Primary Tasks** | Manipulation, Pick & Place, Sorting |
-| **Robot Types** | SO-100 (various colors) |
-| **Data Format** | LeRobot v2.0 and v2.1 dataset format |
-| **Total Size** | 119.3 GB |
-
-## 🗂️ Structure
-
-The dataset maintains a clear hierarchical structure:
-
-```
-community_dataset_v1/
-├── contributor1/
-│   ├── dataset_name_1/
-│   │   ├── data/           # Parquet files with observations
-│   │   ├── videos/         # MP4 recordings
-│   │   └── meta/           # Metadata and info
-│   └── dataset_name_2/
-├── contributor2/
-│   └── dataset_name_3/
-└── ...
-```
-
-Each dataset follows the LeRobot format standard, ensuring compatibility with existing frameworks and easy integration.
-
-## 🏆 Top Contributors
-
-| Contributor | Datasets Quantity |
-|-------------|----------|
-| lirislab | 14 |
-| roboticshack | 9 |
-| sihyun77 | 8 |
-| pierfabre | 7 |
-| ganker5 | 6 |
-| paszea | 5 |
-| samsam0510 | 5 |
-| pranavsaroha | 5 |
-| bensprenger | 4 |
-| Chojins | 4 |
-
-## 🚀 Usage
-
-### Prerequisites
-
-**1. Install LeRobot**
-
-Follow the [official LeRobot installation guide](https://huggingface.co/docs/lerobot/installation):
-
-```bash
-# Create conda environment with Python 3.10
-conda create -y -n lerobot python=3.10
-conda activate lerobot
-
-# Install ffmpeg (required for video processing)
-conda install ffmpeg -c conda-forge
-
-git clone https://github.com/huggingface/lerobot.git
-cd lerobot
-
-# Install LeRobot from Source
-pip install -e .
-```
-
-**2. Authenticate with Hugging Face**
-
-You need to be logged in to access the dataset:
-
-```bash
-# Login to Hugging Face
-huggingface-cli login
-
-# Or alternatively, set your token as an environment variable
-# export HF_TOKEN=your_token_here
-```
-
-Get your token from [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens)
-
-### Download the Dataset
+## Usage
 
 ```python
 from huggingface_hub import snapshot_download
 
-# Download entire collection (requires authentication)
+# Download the entire dataset
 dataset_path = snapshot_download(
     repo_id="HuggingFaceVLA/community_dataset_v1",
     repo_type="dataset",
@@ -130,105 +42,9 @@ dataset_path = snapshot_download(
 )
 ```
 
-### Load Individual Datasets
-
-```python
-from lerobot.datasets.lerobot_dataset import LeRobotDataset
-import os
-
-# Browse available datasets
-for contributor in os.listdir("./community_dataset_v1"):
-    contributor_path = f"./community_dataset_v1/{contributor}"
-    if os.path.isdir(contributor_path):
-        for dataset in os.listdir(contributor_path):
-            print(f"📁 {contributor}/{dataset}")
-
-# Load a specific dataset (requires authentication)
-dataset = LeRobotDataset(
-    repo_id="local",
-    root="./community_dataset_v1/contributor_name/dataset_name"
-)
-
-# Access episodes and observations
-print(f"Episodes: {len(dataset.episode_indices)}")
-print(f"Total frames: {len(dataset)}")
-```
-
-### Integration with SmolVLA
-
-```python
-
-COMING SOON
-# This dataset is designed for training VLA models
-# Compatible with SmolVLA training pipelines
-# needs testing
-
-```
-
-## 🔧 Dataset Format
-
-Each dataset contains:
-
-- **`data/`**: Parquet files with timestamped observations
-  - Robot states (joint positions, velocities)
-  - Action sequences
-  - Camera observations (multiple views)
-  - Language instructions 
-
-- **`videos/`**: Synchronized video recordings
-  - Multiple camera angles
-  - High-resolution capture
-  - Timestamp alignment
-
-- **`meta/`**: Metadata and configuration
-  - Dataset info (fps, episode count)
-  - Robot configuration
-  - Task descriptions
+## Structure
 
-## 🎯 Intended Use
-
-This dataset is designed for:
-
-- **Vision-Language-Action (VLA) model training**
-- **Robotic manipulation research**
-- **Imitation learning experiments**
-- **Multi-task policy development**
-- **Embodied AI research**
-
-## 📈 Revisions
-
-- **v1.0**: Initial community collection
-  - 128 datasets from 55 contributors
-  - Standardized LeRobot format
-  - Quality filtering and validation
-  - Comprehensive metadata
-
-## 🤝 Community Contributions
-
-This dataset exists thanks to the generous contributions from researchers, hobbyists, and institutions worldwide. Each dataset represents hours of careful data collection and curation.
-
-### Contributing Guidelines
-
-Future contributions should follow:
-- LeRobot dataset format
-- Consistent naming conventions for the features, camera views etc.
-- Quality validation checks
-- Proper task descriptions, describing the actions precisely.
-
-Check the [blogpost](https://huggingface.co/blog/lerobot-datasets) for more information 
-
-## 📄 License
-
-Released under Apache 2.0 license. Individual datasets may have additional attribution requirements - please check contributor documentation.
-
-## 🔗 Related Work
-
-- [LeRobot Framework](https://github.com/huggingface/lerobot)
-- [SmolVLA model](https://huggingface.co/lerobot/smolvla_base)
-- [SmolVLA Blogpost](https://huggingface.co/blog/smolvla)
-- [SmolVLA Paper](https://huggingface.co/papers/2506.01844)
-- [Docs](https://huggingface.co/docs/lerobot/smolvla)
-- [How to Build a successful Robotics dataset with Lerobot?](https://huggingface.co/blog/lerobot-datasets)
----
+The dataset preserves the original subfolder structure with user/dataset organization.
 
-*Built with ❤️ by the SmolVLA team and LeRobot Community*
+Size: ~120GB
+Format: LeRobot dataset format