Idk

text-generation.py

@@ -1,6 +1,21 @@
 # text_generation.py
 
-class YourTextGenerationModel:
+import torch
+import torch.nn as nn
+
+class YourTextGenerationModel(nn.Module):
+    def __init__(self, vocab_size, embedding_dim, hidden_dim):
+        super(YourTextGenerationModel, self).__init__()
+        self.embedding = nn.Embedding(vocab_size, embedding_dim)
+        self.lstm = nn.LSTM(embedding_dim, hidden_dim, batch_first=True)
+        self.linear = nn.Linear(hidden_dim, vocab_size)
+
+    def forward(self, x):
+        embedded = self.embedding(x)
+        lstm_out, _ = self.lstm(embedded)
+        output = self.linear(lstm_out)
+        return output
+
     def generate_text(self, prompt):
         # Your text generation logic here
         # Replace this with your actual text generation code
@@ -9,7 +24,11 @@ class YourTextGenerationModel:
 
 if __name__ == "__main__":
     # Example usage of your text generation model
-    your_model = YourTextGenerationModel()
+    vocab_size = 10000  # Replace with your actual vocabulary size
+    embedding_dim = 128  # Replace with your desired embedding dimension
+    hidden_dim = 256  # Replace with your desired hidden dimension
+
+    your_model = YourTextGenerationModel(vocab_size, embedding_dim, hidden_dim)
     prompt = "Once upon a time"
     generated_text = your_model.generate_text(prompt)