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c7ce0085fb
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feat: implement custom Rosie transformer model from scratch
Architecture:
- Custom GPT-style decoder-only transformer (500M params)
- 768 hidden size, 12 layers, 12 attention heads
- 32k vocabulary with BPE tokenizer
- Built-in emotion classification head
- 2048 token context window
Components:
- Multi-head self-attention mechanism
- Feed-forward networks with GELU- Layer normalization and residual connections
- Custom tokenizer with special tokens for emotions/actions
- Generation with temperature, top-k, and nucleus sampling
Training Infrastructure:
- Full training script with data loading
- Gradient clipping and mixed precision support
- Checkpoint management
- Training guide with 3-phase approach:
* Phase 1: Base language (10-50B tokens, 3-7 days)
* Phase 2: Personality fine-tuning (100k-500k examples, 1-2 days)
* Phase 3: Emotion training (50k-100k examples, 6-12 hours)
Integration:
- Inference engine for real-time generation
- Emotion detection from responses
- Conversation history management
- Ready for desktop app and Discord bot integration
No external model dependencies - 100% custom and unbiased
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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2025-09-30 22:46:15 -04:00 |
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