Update README.md

README.md

@@ -15,33 +15,42 @@ train_time: o'rtacha 45 minute.
 
 misol uchun : 
 
-     ``` from datasets import load_dataset 
-         dataset = load_dataset("ybelkada/football-dataset", split="train")```
+```
+    from datasets import load_dataset 
+    dataset = load_dataset("ybelkada/football-dataset", split="train")
+
+```
 
 
 ### Usage model
 
-   ``` from transformers import AutoProcessor, BlipForConditionalGeneration
+```
+from transformers import AutoProcessor, BlipForConditionalGeneration
 
-       processor = AutoProcessor.from_pretrained("ai-nightcoder/Image2text")
-       model = BlipForConditionalGeneration.from_pretrained("ai-nightcoder/Image2text") ```
+processor = AutoProcessor.from_pretrained("ai-nightcoder/Image2text")
+model = BlipForConditionalGeneration.from_pretrained("ai-nightcoder/Image2text")
 
-      #### image olamiz
-      ``` example = dataset[0]
-          image = example["image"]
-          image ```
+```
+# image olamiz
 
+```
+example = dataset[0]
+image = example["image"]
+image
 
-     #### generate qismi.
+```
 
 
-  ```inputs = processor(images=image, return_tensors="pt").to(device)
-    pixel_values = inputs.pixel_values
-    
-    generated_ids = model.generate(pixel_values=pixel_values, max_length=50)
-    generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-    print(generated_caption) ```
+#### generate qismi.
 
+```
+inputs = processor(images=image, return_tensors="pt").to(device)
+pixel_values = inputs.pixel_values
+    
+generated_ids = model.generate(pixel_values=pixel_values, max_length=50)
+generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(generated_caption)
 
+```
 
 **Yuqorida ko'rsatgan tartibda modeldan foydalanishni tavsiya qilaman.**