Create app.py

app.py

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+# Import libraries
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load model and tokenizer
+model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-70b-chat-hf")
+tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-70b-chat-hf")
+
+# Define a function to generate responses
+def chatbot(text):
+# Encode the input text
+input_ids = tokenizer.encode(text + tokenizer.eos_token, return_tensors="pt")
+# Generate a response
+output_ids = model.generate(input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
+# Decode the output
+output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+# Return the output text
+return output_text
+
+# Create a web interface
+iface = gr.Interface(chatbot, "textbox", "text", examples=[["Hello"], ["How are you?"], ["What is your name?"]])
+# Launch the interface
+iface.launch()
+