Update README.md

README.md

@@ -23,6 +23,33 @@ They are over 30% better compared to Amazon Titan Embedding services for e-comme
 | Marqo-Ecommerce-B   | 203 | 768           | Marqo/marqo-ecommerce-embeddings-B | [link](https://marqo-gcl-public.s3.us-west-2.amazonaws.com/marqo-general-ecomm/marqo-ecomm-embeddings-b.pt) |
 | Marqo-Ecommerce-L   | 652 | 1024          | Marqo/marqo-ecommerce-embeddings-L | [link](https://marqo-gcl-public.s3.us-west-2.amazonaws.com/marqo-general-ecomm/marqo-ecomm-embeddings-l.pt)                                       |
 
+### HuggingFace with transformers
+```python
+from transformers import AutoModel, AutoProcessor
+import torch
+from PIL import Image
+import requests
+# model_name= 'Marqo/marqo-ecommerce-embeddings-L'
+model_name = 'Marqo/marqo-ecommerce-embeddings-B'
+
+model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
+processor = AutoProcessor.from_pretrained(model_name, trust_remote_code=True)
+
+img = Image.open(requests.get('https://raw.githubusercontent.com/marqo-ai/marqo-FashionCLIP/main/docs/fashion-hippo.png', stream=True).raw).convert("RGB")
+image = [img]
+text = ["a hat", "a t-shirt", "shoes"]
+processed = processor(text=text, images=image, padding='max_length', return_tensors="pt")
+processor.image_processor.do_rescale = False
+with torch.no_grad():
+    image_features = model.get_image_features(processed['pixel_values'], normalize=True)
+    text_features = model.get_text_features(processed['input_ids'], normalize=True)
+
+    text_probs = (100 * image_features @ text_features.T).softmax(dim=-1)
+    
+print(text_probs)
+# [9.9955e-01, 4.4712e-04, 4.4010e-06]]
+```
+
 ### HuggingFace with OpenCLIP
 ```
 pip install open_clip_torch
@@ -56,32 +83,6 @@ with torch.no_grad(), torch.cuda.amp.autocast():
 print("Label probs:", text_probs)
 # [9.9955e-01, 4.4712e-04, 4.4010e-06]]
 ```
-### HuggingFace with transformers
-```python
-from transformers import AutoModel, AutoProcessor
-import torch
-from PIL import Image
-import requests
-# model_name= 'Marqo/marqo-ecommerce-embeddings-L'
-model_name = 'Marqo/marqo-ecommerce-embeddings-B'
-
-model_1 = AutoModel.from_pretrained(model_name, trust_remote_code=True)
-processor_1 = AutoProcessor.from_pretrained(model_name, trust_remote_code=True)
-
-img = Image.open(requests.get('https://raw.githubusercontent.com/marqo-ai/marqo-FashionCLIP/main/docs/fashion-hippo.png', stream=True).raw).convert("RGB")
-image_1 = [img]
-text_1 = ["a hat", "a t-shirt", "shoes"]
-processed_1 = processor_1(text=text_1, images=image_1, padding='max_length', return_tensors="pt")
-processor_1.image_processor.do_rescale = False
-with torch.no_grad():
-    image_features_1 = model_1.get_image_features(processed_1['pixel_values'], normalize=True)
-    text_features_1 = model_1.get_text_features(processed_1['input_ids'], normalize=True)
-
-    text_probs_1 = (100 * image_features_1 @ text_features_1.T).softmax(dim=-1)
-    
-print(text_probs_1)
-# [9.9955e-01, 4.4712e-04, 4.4010e-06]]
-```
 
 ### Evaluation with GCL
 ```