PRATYUSH-BHARDWAJ/Cortex-A-0.5

🧠 Cortex-A 0.5 — live latent-AR playground

This Space serves the latest weights of Cortex-A 0.5, a ~0.73B two-level language model pre-trained from scratch in JAX/Flax on a single TPU v5e-8.

• —A deep latent-AR planner (32 layers over 5-token chunks) predicts the next chunk embedding through a KV-cached decode.
• —A shallow AR writer decodes each token conditioned on the full planner plan (cond_fuse(concat(token, plan))), the planner advancing once per 5-token chunk.
• —A tied/factorized head reads the tokens out — standard next-token decoding.

The latent backbone is always on: its plan conditions every generated token, so what you see is the real two-level pipeline, not the writer alone. It's a base model — type the start of a sentence and it continues it.