Update README.md

README.md

@@ -137,6 +137,42 @@ QNetworkGPT2 is an extraordinary AI model that marries Reinforcement Learning (R
 4. Assess the text with metrics and demands.
 5. Fine-tune and enhance for your text generation quest.
 
+---
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("ayjays132/QNetworkGPT2")
+model = AutoModelForCausalLM.from_pretrained("ayjays132/QNetworkGPT2")
+
+# Initialize a conversation history
+conversation_history = []
+
+# Start a conversation loop
+while True:
+    # Get user input
+    user_input = input("You: ")
+
+    # Add user input to the conversation history
+    conversation_history.append(user_input)
+
+    # Concatenate the conversation strings
+    conversation_text = " ".join(conversation_history)
+
+    # Tokenize and pad the input
+    input_ids = tokenizer.encode(conversation_text, return_tensors="pt", padding=True, truncation=True)
+
+    # Generate a response
+    output_ids = model.generate(input_ids, max_length=150, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
+
+    # Decode the generated response
+    generated_response = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+
+    # Print the generated response
+    print("Bot:", generated_response)
+
+    # Add bot's response to the conversation history
+    conversation_history.append(generated_response)
+---
 ## Explore and Create
 
 QNetworkGPT2 is your ticket to exploring new horizons in text generation. From chatbots and content creation to storytelling and beyond, it's your AI companion for all text adventures. 🌟