Repository navigation
CrystalLM
🚀 Vocabulary-Governed GRU Release
This release marks a structural stabilization milestone for CrystalLM.
✨ Highlights
-
GRU-based word-level language model
- Replaced earlier experimental RNN variants with a stable multi-layer GRU
- Improved training stability and long-context behavior
-
Vocabulary governance refined
- Explicit low-frequency pruning
- More controlled
<UNK>mapping - Reduced vocabulary noise and improved generation coherence
-
Generation behavior improved
- Fixed premature
<END>termination - Temperature sampling behavior is now consistent and predictable
- Fixed premature
-
Training workflow hardened
- More stable loss convergence
- CPU-friendly training path (Intel Mac verified)
- Checkpoint reuse without retraining
🎯 Scope & Intent
This release prioritizes clarity, correctness, and observability over scale.
It represents a solid educational baseline for understanding word-level language modeling before moving to Transformers.