Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load a smaller model for CPU usage
+MODEL_NAME = "mistralai/Mistral-7B-Instruct"
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.float32, device_map="cpu")
+
+def chat_with_ai(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to("cpu")
+    output = model.generate(**inputs, max_length=200)
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    return response
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=chat_with_ai,
+    inputs=gr.Textbox(placeholder="Ask me anything..."),
+    outputs=gr.Textbox()
+)
+
+demo.launch()