Create CHST.PY

CHST.PY

@@ -0,0 +1,41 @@
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+import torch
+
+# Load pre-trained model and tokenizer
+model_name = "gpt2"  # You can use other models like "gpt2-medium", "gpt2-large", etc.
+model = GPT2LMHeadModel.from_pretrained(model_name)
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+
+# Add special tokens if using specific fine-tuned models
+tokenizer.pad_token = tokenizer.eos_token
+model.resize_token_embeddings(len(tokenizer))
+
+# Device configuration (use GPU if available)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+# Function to generate AI response
+def get_ai_response(user_input):
+    # Tokenize input and encode it
+    inputs = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors="pt").to(device)
+
+    # Generate response (max_length can be adjusted)
+    outputs = model.generate(inputs, max_length=150, num_return_sequences=1, no_repeat_ngram_size=2, top_p=0.95, temperature=0.7)
+
+    # Decode response
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Main chatbot loop
+print("AI Chatbot is ready to talk! Type 'quit' to end the conversation.")
+while True:
+    user_input = input("You: ")
+    
+    # Exit condition
+    if user_input.lower() == 'quit':
+        print("AI Chatbot: Goodbye!")
+        break
+    
+    # Get AI response
+    ai_response = get_ai_response(user_input)
+    print(f"AI Chatbot: {ai_response}")