Upload model_architecture.py with huggingface_hub

model_architecture.py

@@ -0,0 +1,32 @@
+import torch
+import torch.nn as nn
+
+class StockPredictor(nn.Module):
+    def __init__(self, input_size, hidden_size=128, num_layers=2, dropout=0.3):
+        super(StockPredictor, self).__init__()
+        
+        self.lstm = nn.LSTM(
+            input_size=input_size,
+            hidden_size=hidden_size,
+            num_layers=num_layers,
+            batch_first=True,
+            dropout=dropout
+        )
+        
+        self.fc1 = nn.Linear(hidden_size, 64)
+        self.fc2 = nn.Linear(64, 32)
+        self.fc3 = nn.Linear(32, 1)
+        self.relu = nn.ReLU()
+        self.dropout = nn.Dropout(dropout)
+        
+    def forward(self, x):
+        lstm_out, _ = self.lstm(x)
+        last_output = lstm_out[:, -1, :]
+        
+        x = self.relu(self.fc1(last_output))
+        x = self.dropout(x)
+        x = self.relu(self.fc2(x))
+        x = self.dropout(x)
+        x = self.fc3(x)
+        
+        return x