Update README.md

README.md

@@ -7,4 +7,27 @@ library_name: transformers
 pipeline_tag: fill-mask
 tags:
 - code
----
+---
+import torch
+from torch import nn
+# Definir la red,  lo que en definitiva la hace siamesa es pasar los dos dic
+class SBERT(nn.Module):
+    def __init__(self, base_model, dropout=0.1):
+        super().__init__()
+        self.base_model = base_model
+        self.dropout = nn.Dropout(dropout)
+        # Recordamos que la salida de la Bert es 768
+        #self.fc = nn.Linear(768, 3) #Cambio 13/6
+        self.fc = nn.Linear(768*3, 3)
+
+    def forward(self, premise, hypothesis):
+        out_u = self.base_model(**premise)
+        out_v = self.base_model(**hypothesis)
+        pooler_u = out_u.pooler_output
+        pooler_v = out_v.pooler_output
+        pooler_u = self.dropout(pooler_u)
+        pooler_v = self.dropout(pooler_v)
+        #concatenated = torch.cat([self.fc(pooler_u), self.fc(pooler_v), torch.abs(self.fc(pooler_u) - self.fc(pooler_v))], dim=0)
+        concatenated = torch.cat([pooler_u, pooler_v, torch.abs(pooler_u -pooler_v)], dim=1)
+        out=self.fc(concatenated)
+        return out