Cannot isolate instruct tuning vs architecture (sliding window, KV sharing, logit softcapping) with current test matrix. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Tommi Niemi / Rotko Networks Hidden-state episodic memory for frozen transformers. No gradients. Teach via one forward pass, recall via cosine similarity + logit injection. 200-line Python reproduction included. pip install transformers torch numpy && python python/epimem.py