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+ # Humanoid-Web3-IntentNet-v2
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+
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+ ## Overview
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+ Humanoid-Web3-IntentNet-v2 is an advanced lightweight NLP model built to translate natural language commands into structured humanoid robot action intents.
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+
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+ The model is optimized for robotics automation and Web3-based AI integration, enabling real-time action execution and blockchain logging compatibility.
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+
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+ ## Model Architecture
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+ - Base Model: DistilBERT
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+ - Framework: PyTorch
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+ - Task: Intent Classification
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+ - Language: English
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+ - Max Sequence Length: 128
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+ - Labels: 6 action classes
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+
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+ ## Supported Actions
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+ - move_object
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+ - pick_and_place
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+ - rotate_object
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+ - scan_object
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+ - start_action
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+ - stop_action
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+
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+ ## Example
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+
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+ Input:
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+ "Scan the QR code and move the device to the table."
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+
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+ Output:
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+ {
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+ "action": "scan_object",
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+ "object": "QR code",
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+ "destination": "table"
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+ }
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+
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+ ## Use Cases
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+ - Humanoid robotics control
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+ - Web3 AI agents
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+ - Smart factory automation
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+ - Blockchain-based activity logging
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+
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+ ## Tags
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+ robotics
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+ humanoid-ai
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+ web3-ai
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+ intent-classification
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+ automation