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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
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