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TinyBrowser GNM (Goal Navigation Model)
Lightweight CNN for on-device browser action prediction. Takes V3 semantic grid [1,32,64,8] + goal vector [1,64] → heatmap + 13 action classes.
Architecture
- Input: V3 Frame (uint8) + Goal embedding (float32)
- Output: Heatmap [1,1,32,64] (WHERE) + Action logits [1,13] (WHAT)
- Inference: <0.5ms on Hexagon HTP, <5ms on CPU
Files
gnm_best.pth— PyTorch checkpointgnm_fp32.onnx— ONNX for ONNX Runtime (QNN EP / NNAPI / CPU)
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