Create main.py

main.py

@@ -0,0 +1,28 @@
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+import torch
+
+# Load the GPT2 tokenizer and model
+tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
+model = GPT2LMHeadModel.from_pretrained('gpt2')
+
+# Load the training data
+with open('train.txt', 'r') as f:
+    text = f.read()
+
+# Tokenize the training data
+input_ids = tokenizer.encode(text, return_tensors='pt')
+
+# Train the model
+optimizer = torch.optim.Adam(model.parameters(), lr=5e-5)
+model.train()
+for i in range(100):
+    outputs = model(input_ids, labels=input_ids)
+    loss = outputs[0]
+    loss.backward()
+    optimizer.step()
+    optimizer.zero_grad()
+
+    print(f'Epoch {i+1}, Loss: {loss.item()}')
+
+# Save the trained model
+model.save_pretrained('my_gpt_model')