Upload README.md with huggingface_hub

README.md

@@ -11,14 +11,15 @@ with no imagery or labels at inference; the embedding is Matryoshka-structured,
 deploy width.
 
 ## Files
-- `mind.pt` - trained ReSIREN encoder (embed_dim 3072, depth 12). Load with `mind_standalone.load_mind`.
+- `mind.safetensors` - recommended weights, fp16 (227 MB, safe / no-pickle). Load with `mind_standalone.load_mind`.
+- `mind.pt` - fp32 weights (454 MB) for exact reproduction.
 - `mind.onnx` (+ `mind.onnx.data`) - ONNX graph for onnxruntime / TensorRT (input `latlon` [N,2], dynamic batch).
 - `mind.pt2` - torch ExportedProgram; load with `torch.export.load`.
 
 ## Usage
 ```python
 from mind_standalone import load_mind, embed   # github.com/taylor-geospatial/mind
-emb = embed(load_mind("mind.pt"), lats, lons)  # [N, 64]; half=True for ~12x on GPU
+emb = embed(load_mind("mind.safetensors"), lats, lons)  # [N, 64]; half=True for ~12x on GPU
 ```
 Build a TensorRT engine from the ONNX with `trtexec --onnx=mind.onnx --saveEngine=mind.trt --fp16`.
 Code and paper: https://github.com/taylor-geospatial/mind