Update README.md

README.md

@@ -94,6 +94,40 @@ model = AutoModel.from_pretrained(
     trust_remote_code=True,
 ).eval().cuda()
 
+#!wget https://huggingface.co/5CD-AI/ColVintern-1B-v1/resolve/main/ex1.jpg
+#!wget https://huggingface.co/5CD-AI/ColVintern-1B-v1/resolve/main/ex2.jpg
+
+images = [Image.open("ex1.jpg"),Image.open("ex2.jpg")]
+batch_images = processor.process_images(images)
+
+queries = [
+    "Cảng Hải Phòng thông báo gì ?",
+    "Phí giao hàng bao nhiêu ?",
+]
+
+batch_queries = processor.process_queries(queries) 
+
+batch_images["pixel_values"] =  batch_images["pixel_values"].cuda().bfloat16()
+batch_images["input_ids"] = batch_images["input_ids"].cuda() 
+batch_images["attention_mask"] = batch_images["attention_mask"].cuda().bfloat16()
+batch_queries["input_ids"] = batch_queries["input_ids"].cuda() 
+batch_queries["attention_mask"] = batch_queries["attention_mask"].cuda().bfloat16()
+
+with torch.no_grad():
+    image_embeddings = model(**batch_images)
+    query_embeddings = model(**batch_queries)
+
+scores = processor.score_multi_vector(query_embeddings, image_embeddings)
+
+max_scores, max_indices = torch.max(scores, dim=1)
+# In ra kết quả cho mỗi câu hỏi
+for i, query in enumerate(queries):
+    image_name = images[max_indices[i]]
+    print(f"Câu hỏi: '{query}'")
+    print(f"Điểm số: {max_scores[i].item()}\n")
+    plt.figure(figsize=(5,5))
+    plt.imshow(image_name)
+    plt.show()
 ```
 
 ## Citation