Create app.py

app.py

@@ -0,0 +1,20 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load model and tokenizer
+model_name = "meta-llama/Llama-3.2-1B"  # Replace with the correct model name if necessary
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Define inference function
+def generate_text(input_text):
+    inputs = tokenizer(input_text, return_tensors="pt")
+    outputs = model.generate(inputs["input_ids"], max_length=50, num_return_sequences=1)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Create Gradio interface
+iface = gr.Interface(fn=generate_text, inputs="text", outputs="text")
+
+# Launch the interface
+iface.launch()