Add back README.md with updated FPS info

README.md

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+---
+title: Neural Pong
+emoji: 🎮
+colorFrom: blue
+colorTo: purple
+sdk: docker
+pinned: false
+license: mit
+---
+
+# Neural Pong
+
+A real-time Pong game where frames are generated by a diffusion model trained with rectified flow matching. Control the blue paddle using arrow keys or WASD to play!
+
+## Features
+
+- **Real-time frame generation**: Uses a frame-autoregressive transformer with diffusion sampling
+- **Interactive gameplay**: Control the paddle with keyboard inputs
+- **Configurable parameters**: Adjust FPS and diffusion steps
+- **Low-latency streaming**: Achieves ~12 FPS with 4 diffusion steps
+
+## How to Play
+
+1. Wait for the model to load (you'll see a loading spinner)
+2. Click "Start Stream" to begin generating frames
+3. Use **Arrow Keys** or **WASD** to control the blue paddle:
+   - **Up/W**: Move paddle up
+   - **Down/S**: Move paddle down
+4. Adjust the FPS and diffusion steps using the controls
+5. Click "Stop Stream" when done
+
+## Technical Details
+
+This demo uses a small transformer model trained with rectified flow matching to simulate Pong game frames conditioned on user inputs. The model generates 24×24 pixel frames in real-time using diffusion sampling with configurable steps.
+
+## Model Architecture
+
+- Frame-autoregressive transformer
+- Rectified flow matching training
+- Caching for efficient inference
+- GPU-accelerated generation
+