Update app.py

app.py

@@ -1,3 +1,33 @@
+# Import necessary libraries
+from transformers import AutoModelForCausalLM, AutoTokenizer
 import gradio as gr
 
-gr.load("models/meta-llama/Llama-2-7b-chat-hf").launch()
+# Load the model and tokenizer
+model_name = "meta-llama/Llama-2-7b-chat-hf"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Define the chat function
+def chat_with_llama2(input_text):
+    inputs = tokenizer(input_text, return_tensors="pt")
+    outputs = model.generate(inputs["input_ids"], max_length=512, do_sample=True, top_p=0.95, top_k=60)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=chat_with_llama2,
+    inputs="text",
+    outputs="text",
+    title="LLaMa 2 Chat HF",
+    description="Chat with LLaMa 2 model using Hugging Face Transformers and Gradio.",
+    examples=[
+        ["Hello, LLaMa 2! How are you today?"],
+        ["Can you tell me a joke?"],
+        ["What is the capital of France?"]
+    ]
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    interface.launch()