Experimental playground for benchmarking language model (LM) architectures, layers, and tricks on smaller datasets. Designed for flexible experimentation and exploration.
-
Updated
May 6, 2026 - Python
Experimental playground for benchmarking language model (LM) architectures, layers, and tricks on smaller datasets. Designed for flexible experimentation and exploration.
Integrated mechanistic interpretability + sparse autoencoder framework for Hybrid SSM-Attention models (Mamba-2, Hymba, RWKV-7). v0.1.2 alpha: real forward-pass intervention + mean-ablation patching shipped, CPU smoke; GPU/real adapters in v0.2.
Add a description, image, and links to the hymba topic page so that developers can more easily learn about it.
To associate your repository with the hymba topic, visit your repo's landing page and select "manage topics."