Add README.md

README.md

@@ -1,13 +1,27 @@
 ---
-title: Tessera Comparison
-emoji: 🏃
-colorFrom: green
-colorTo: gray
+title: Tessera-1B-Nano comparison
+emoji: 🧩
+colorFrom: gray
+colorTo: blue
 sdk: gradio
-sdk_version: 6.28.0
-python_version: '3.12'
+sdk_version: 4.44.1
 app_file: app.py
-pinned: false
+suggested_hardware: zero-a10g
+license: apache-2.0
+short_description: Side-by-side generation with a live concept readout
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Tessera-1B-Nano vs Tessera-1B-Nano-Base
+
+Side-by-side demo for the token-matched comparison described in the
+[Tessera-1B-Nano repository](https://github.com/yava-code/Tessera-1B-Nano). Three generations per run:
+the NTP-only baseline, the concept arm with predicted feedback, andthe concept arm with its concept feedback zeroed at inference. A readout panel reports the teacher-forced NTP
+loss of each model on the prompt and the zero-feedback penalty of the concept arm.
+
+Runs on ZeroGPU: the checkpoints load on CPU at startup and each request moves compute to
+a shared A100 through the `spaces.GPU` decorator.
+
+The checkpoints: [Tessera-1B-Nano](https://huggingface.co/yava-code/Tessera-1B-Nano) and
+[Tessera-1B-Nano-Base](https://huggingface.co/yava-code/Tessera-1B-Nano-Base). The full
+study, including the committed intervention numbers (zeroing costs +0.1050 nats on held-out
+data, shuffling costs +0.0008), is in the repository whitepaper.