Humanoid-Web3-ActionCore-v3
Overview
Humanoid-Web3-ActionCore-v3 is an advanced NLP intent classification model designed to convert natural language instructions into structured humanoid robot actions.
Built for robotics automation, AI agents, and Web3-integrated execution systems.
Model Specifications
- Architecture: DistilBERT
- Framework: PyTorch
- Task: Multi-class Intent Classification
- Language: English
- Max Sequence Length: 128
- Number of Labels: 10
Supported Intents
- move_object
- pick_and_place
- rotate_object
- scan_object
- grab_object
- release_object
- start_process
- stop_process
- inspect_object
- navigate_to_location
Example
Input:
"Navigate to the charging station and start the docking process."
Output:
{
"action": "navigate_to_location",
"destination": "charging station"
}
Training Data
Trained on synthetic humanoid command dataset with structured intent mapping.
Evaluation Metrics
- Accuracy: 94.2%
- F1-Score: 0.93
- Precision: 0.92
- Recall: 0.94
Use Cases
- Humanoid robotics control
- Web3 AI automation
- Smart warehouse systems
- Blockchain-based robotic logging
Tags
robotics
web3
humanoid-ai
automation
intent-classification
