# Humanoid-Web3-IntentNet-v2

## Overview
Humanoid-Web3-IntentNet-v2 is an advanced lightweight NLP model built to translate natural language commands into structured humanoid robot action intents.

The model is optimized for robotics automation and Web3-based AI integration, enabling real-time action execution and blockchain logging compatibility.

## Model Architecture
- Base Model: DistilBERT
- Framework: PyTorch
- Task: Intent Classification
- Language: English
- Max Sequence Length: 128
- Labels: 6 action classes

## Supported Actions
- move_object
- pick_and_place
- rotate_object
- scan_object
- start_action
- stop_action

## Example

Input:
"Scan the QR code and move the device to the table."

Output:
{
  "action": "scan_object",
  "object": "QR code",
  "destination": "table"
}

## Use Cases
- Humanoid robotics control
- Web3 AI agents
- Smart factory automation
- Blockchain-based activity logging

## Tags
robotics
humanoid-ai
web3-ai
intent-classification
automation