Update README.md

README.md

@@ -4,14 +4,14 @@ license: mit
 
 This is the structure of the BLIPNet model. You can load the model with it, or you can create a bigger model for your task.
 
-class BLIPNet(torch.nn.Module):
+  class BLIPNet(torch.nn.Module):
     def __init__(self, ):
         super().__init__()
         #Generation Model
         self.model = BlipForConditionalGeneration.from_pretrained(MODEL_NAME, cache_dir="model")
         #Same with https://huggingface.co/uf-aice-lab/BLIP-Math
         self.ebd_dim = ebd_dim= 443136
-
+        
         #Classification Model
         fc_dim = 64  # You can choose a higher number for better performance, for example, 1024.
         self.head = nn.Sequential(
@@ -19,8 +19,7 @@ class BLIPNet(torch.nn.Module):
             nn.ReLU(), 
         )
         self.score = nn.Linear(fc_dim, 5) #5 classes
-
-
+        
     def forward(self, pixel_values, input_ids):
         outputs = self.model(input_ids=input_ids, pixel_values=pixel_values, labels=input_ids)
         image_text_embeds = self.model.vision_model(pixel_values, return_dict=True).last_hidden_state