Upload model.py

model.py

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+import torch
+import torch.nn as nn
+
+class VotePredictor(nn.Module):
+    def __init__(self, text_dim=384, country_count=193, country_emb_dim=32, hidden_dim=256):
+        super(VotePredictor, self).__init__()
+        self.country_embedding = nn.Embedding(country_count, country_emb_dim)
+        self.model = nn.Sequential(
+            nn.Linear(text_dim + country_emb_dim, hidden_dim),
+            nn.ReLU(),
+            nn.Dropout(0.3),
+            nn.Linear(hidden_dim, 1)
+        )
+
+    def forward(self, text_vecs, country_ids):
+        country_vecs = self.country_embedding(country_ids)
+        x = torch.cat([text_vecs, country_vecs], dim=1)
+        return self.model(x)