Create app.py

app.py

@@ -0,0 +1,35 @@
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import gradio as gr
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen-350M-multi")
+model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-multi")
+
+def generate_code(prompt):
+    # Tokenize the input text
+    input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+
+    # Generate code based on the input text
+    generated_ids = model.generate(
+        input_ids,
+        max_length=200,  # Adjust as needed
+        num_return_sequences=1,  # Number of generated sequences to return
+        pad_token_id=tokenizer.eos_token_id  # Handle padding tokens
+    )
+
+    # Decode the generated tokens to text
+    generated_code = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
+    return generated_code
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=generate_code,
+    inputs=gr.Textbox(lines=2, placeholder="Enter your code prompt here..."),
+    outputs="text",
+    title="Code Generator",
+    description="Generate code snippets using the Salesforce CodeGen model."
+)
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    iface.launch()