Update README.md

README.md

@@ -39,6 +39,22 @@ The model can be seamlessly used with [OpenCLIP](https://github.com/mlfoundation
 import open_clip
 model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:Marqo/marqo-fashionSigLIP')
 tokenizer = open_clip.get_tokenizer('hf-hub:Marqo/marqo-fashionSigLIP')
+
+import torch
+from PIL import Image
+
+image = preprocess_val(Image.open("docs/fashion-hippo.png")).unsqueeze(0)
+text = tokenizer(["a hat", "a t-shirt", "shoes"])
+
+with torch.no_grad(), torch.cuda.amp.autocast():
+    image_features = model.encode_image(image)
+    text_features = model.encode_text(text)
+    image_features /= image_features.norm(dim=-1, keepdim=True)
+    text_features /= text_features.norm(dim=-1, keepdim=True)
+
+    text_probs = (100.0 * image_features @ text_features.T).softmax(dim=-1)
+
+print("Label probs:", text_probs)
 ```
 
 ## Benchmark Results