updated README

README.md

@@ -7,27 +7,29 @@ tags:
 - brain-mri
 - tinygrad
 - skull-stripping
-license: apache-2.0
+license: mit
 pipeline_tag: image-segmentation
-datasets:
-- openneuro/ds003800
 ---
 
 # MindGrab (BrainChop MeshNet)
 
-MindGrab is a MeshNet-based skull-stripping model from the [BrainChop](https://github.com/neuroneural/brainchop) project. It takes 256^3 conformed T1 volumes and produces a binary brain mask. The checkpoint runs entirely in [tinygrad](https://github.com/tinygrad/tinygrad) and powers the in-browser BrainChop demos (WebGPU/WebGL).
+MindGrab is a MeshNet-based skull-stripping model from the
+[BrainChop](https://github.com/neuroneural/brainchop) project. It takes 256^3
+conformed T1 volumes and produces a binary brain mask. The checkpoint runs
+entirely in [tinygrad](https://github.com/tinygrad/tinygrad) and powers the
+in-browser BrainChop demos (WebGPU/WebGL).
 
 ## Files
 
-| File | Description |
-|------|-------------|
-| `model.json` | MeshNet architecture definition (in/out channels, kernel sizes, bias, dropout flags). |
-| `layers.json` | Original layer configuration (handy for exporters / analyzers). |
-| `model.pth` | FP32 PyTorch/ tinygrad checkpoint (~0.6 MB). |
+| File          | Description |
+|------         |-------------|
+| `model.json`  | MeshNet architecture definition (in/out channels, kernel sizes, bias, dropout flags). |
+| `layers.json` | Optional Layer configs |
+| `model.pth`   | FP32 PyTorch checkpoint |
 
-Optionally, you can upload the WebGPU export (`net_mindgrab.js` + `net_mindgrab.safetensors`) from [`niivue-tinygrad`](https://github.com/spikedoanz/niivue-tinygrad) if you want to distribute browser-ready assets alongside the raw weights.
 
-Optionally, you can also run the model through the official frontend at [brainchop.org](https://brainchop.org/)
+Optionally, you can also run the model through the official frontend at
+[brainchop.org](https://brainchop.org/)
 
 
 ## Usage