Hey, I wanted to share a fascinating project, our first attempt at tackling LLM hallucinations : Tilelli LLM. Key Specs & Features: Per-Token Routing: Uses 3 specialized pathways instead of a monolithic architecture. High Honesty Rate: Catches gibberish at an AUROC of 0.93 and refuses cleanly out of distribution. Ternary : Active development on a ternary version is already bridging the performance gap with standard float models. If you want an inspectable, tiny model to study, fork, or deploy for cheap, everything is hosted transparently. Available in GitHub and HuggingFace. https://github.com/TilelliLab/Tilelli-llm From Morocco 🇲🇦 with love. Thanks for your time. submitted by /u/themoroccanship
Originally posted by u/themoroccanship on r/ArtificialInteligence