Upload CohereLabs_command-a-vision-07-2025_0.py with huggingface_hub

CohereLabs_command-a-vision-07-2025_0.py

@@ -14,6 +14,46 @@
 try:
     from huggingface_hub import login
     login(new_session=False)
+    
+    # Use a pipeline as a high-level helper
+    from transformers import pipeline
+    
+    pipe = pipeline("image-text-to-text", model="CohereLabs/command-a-vision-07-2025")
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
+                {"type": "text", "text": "What animal is on the candy?"}
+            ]
+        },
+    ]
+    pipe(text=messages)
+    
+    # Load model directly
+    from transformers import AutoProcessor, AutoModelForImageTextToText
+    
+    processor = AutoProcessor.from_pretrained("CohereLabs/command-a-vision-07-2025")
+    model = AutoModelForImageTextToText.from_pretrained("CohereLabs/command-a-vision-07-2025")
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
+                {"type": "text", "text": "What animal is on the candy?"}
+            ]
+        },
+    ]
+    inputs = processor.apply_chat_template(
+    	messages,
+    	add_generation_prompt=True,
+    	tokenize=True,
+    	return_dict=True,
+    	return_tensors="pt",
+    ).to(model.device)
+    
+    outputs = model.generate(**inputs, max_new_tokens=40)
+    print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
     with open('CohereLabs_command-a-vision-07-2025_0.txt', 'w') as f:
         f.write('Everything was good in CohereLabs_command-a-vision-07-2025_0.txt')
 except Exception as e: