Update similarity_utils.py

similarity_utils.py

@@ -18,14 +18,14 @@ np.random.seed(seed)
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 # Load model for computing embeddings..
-model_ckpt = "nateraw/vit-base-beans"
+model_ckpt = "gjuggler/swin-tiny-patch4-window7-224-finetuned-birds"
 extractor = AutoFeatureExtractor.from_pretrained(model_ckpt)
 
 # Data transformation chain.
 transformation_chain = T.Compose(
     [
         # We first resize the input image to 256x256 and then we take center crop.
-        T.Resize(int((256 / 224) * extractor.size["height"])),
+        T.Resize(224),
         T.CenterCrop(extractor.size["height"]),
         T.ToTensor(),
         T.Normalize(mean=extractor.image_mean, std=extractor.image_std),