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

1. move_object
2. pick_and_place
3. rotate_object
4. scan_object
5. grab_object
6. release_object
7. start_process
8. stop_process
9. inspect_object
10. 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