Updated Model Inference Information

README.md

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+### Train Dataset Means and stds
+lat_mean = 39.951572994535354
+lat_std = 0.0006556104083785816
+lon_mean = -75.19137012508818
+lon_std = 0.0006895844560639971
+
+### Custom Model Class
+from transformers import ViTModel
+class ViTGPSModel(nn.Module):
+    def __init__(self, output_size=2):
+        super().__init__()
+        self.vit = ViTModel.from_pretrained("google/vit-base-patch16-224-in21k")
+        self.regression_head = nn.Linear(self.vit.config.hidden_size, output_size)
+
+    def forward(self, x):
+        cls_embedding = self.vit(x).last_hidden_state[:, 0, :]
+        return self.regression_head(cls_embedding)
+
+### Running Inference
+
+model_path = hf_hub_download(repo_id="Latitude-Attitude/vit-gps-coordinates-predictor", filename="vit-gps-coordinates-predictor.pth")
+model = torch.load(model_path)
+model.eval() 
+
+with torch.no_grad():
+    for images in dataloader:
+        images = images.to(device)
+        outputs = model(images)
+        preds = outputs.cpu() * torch.tensor([lat_std, lon_std]) + torch.tensor([lat_mean, lon_mean])

vit-gps-coordinates-predictor.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d832691c95c0cf6a291c7611d881524494eac520c3a2f8d39c321cf5b5de193d
+size 345686610