Create app.py

app.py

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+from transformers import AutoModelForCausalLM, AutoTokenizer
+import gradio as gr
+
+# Load the model and tokenizer
+model_name = "microsoft/phi-4"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+def predict(input_text):
+    # Tokenize input and generate text
+    inputs = tokenizer(input_text, return_tensors="pt")
+    outputs = model.generate(**inputs)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(label="Input Text"),
+    outputs=gr.Textbox(label="Generated Output"),
+    title="Phi-4 Model",
+    description="Generate text using the microsoft/phi-4 model."
+)
+
+# Launch the interface
+interface.launch()