# BitTransformerLM v0.1.0 - Experimental Research Release

**Release Date:** August 2025  
**Status:** Open Source Research Implementation  
**License:** AGPLv3 + Commercial Licensing Available  

## What's Included

This release provides a complete experimental framework for bit-native language modeling research:

- **Core Architecture:** 57 Python files implementing bit-native transformer with reversible layers
- **Safety Systems:** Real-time K/C/S telemetry and monitoring
- **Research Tools:** Interactive dashboard, distributed training, comprehensive testing
- **Documentation:** Professional model card, research status, and validation reports

## Important Notes

⚠️ **Experimental Status:** This is research code requiring rigorous baseline validation  
⚠️ **Not Production Ready:** Needs extensive evaluation vs standard transformers  
⚠️ **Research Use Only:** Intended for academic investigation and experimentation  

## Licensing

- **Open Source:** AGPLv3 for research and open source use
- **Commercial:** Contact contact@wcnegentropy.com for commercial licensing

## Next Steps

The research community is invited to:
1. Conduct rigorous baseline comparisons vs standard transformers
2. Evaluate on established language modeling benchmarks  
3. Validate (or refute) claimed memory efficiency benefits
4. Share findings openly to advance the field

**Research responsibly. Validate rigorously. Share openly.**