Views
No views yet
model.onnx from this repo and runs it client-side via onnxruntime-web + WebGPU)
💻 Source: https://github.com/gmmeyer/gptbird| File | What |
|---|---|
model.onnx | The ~11M-param "small" model (full game with pipes). ONNX opset 17, dynamic sequence length, returns last-position logits. This is what the web demo runs. |
config.json | Tokenizer offsets, quantization bins, and engine geometry — everything the JS decode loop and renderer need. |
small_pipes.pt | PyTorch checkpoint for model.onnx (n_layer 6, d_model 384, ctx 256 frames). |
nano_nopipes.pt | PyTorch checkpoint for the ~1.9M-param Phase-2 model (bird + gravity + flap, no pipes). |
bird_y, pipe_dx, gap_y, status — generated with slot-constrained
decoding: logits are masked to the legal id range for each field, so a malformed frame is
impossible by construction. The gap_y slot is sampled (a newly revealed pipe's gap is
genuinely unpredictable, so the dream invents one); the other slots are greedy.bird_y: 98.6% exact / 100% within ±1 bin (held-out).gap_y: 99.96% exact on stable frames; 100% validity on RNG spawn frames.