Create app.py

app.py

@@ -0,0 +1,31 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load model and tokenizer
+model_name = "meta-llama/CodeLlama-7b-hf"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Define the inference function
+def generate_code(prompt):
+    # Tokenize the input prompt
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, padding=True)
+    
+    # Generate code using the model
+    outputs = model.generate(inputs["input_ids"], max_length=100, num_return_sequences=1)
+    
+    # Decode the generated output to a string
+    generated_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return generated_code
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=generate_code, 
+    inputs="text", 
+    outputs="text",
+    title="CodeLlama-7b Python Code Generator",
+    description="Generate Python code using the CodeLlama-7b model. Simply input a prompt and get back the generated code.",
+)
+
+# Launch the Gradio interface
+interface.launch()