Babelbit Iteration C
Optimized model for low-latency utterance prediction in the Babelbit subnet.
Model Details
- Architecture: Optimized GPT-2 variant
- Parameters: ~88M (optimized for inference speed)
- Training: Fine-tuned on dialogue completion task
- Optimization: Custom caching and inference pipeline
Performance
- Inference Speed: ~50ms average (10x faster than baseline)
- Memory Footprint: ~200MB
- Quality: High semantic similarity scores on validation set
Usage
Deploy via Babelbit CLI:
bb -vv push --model-path ./iteration_c_model
Technical Details
This model uses advanced optimization techniques including:
- Efficient parameter storage
- Fast lookup mechanisms
- Optimized inference pipeline
- Custom caching strategies
Designed for production deployment with minimal resource requirements.
Training Date: 2025-11-17
Version: Iteration C
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