Create app.py

app.py

@@ -0,0 +1,20 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the model and tokenizer
+model_name = "mistralai/Mistral-Nemo-Instruct-2407"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+def generate_response(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(**inputs, max_length=150, num_return_sequences=1)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Define the Gradio interface
+def chat_function(user_input):
+    return generate_response(user_input)
+
+# Launch the Gradio app
+gr.ChatInterface(fn=chat_function, title="Mistral Chatbot").launch(share=True)