added files

app.py

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+from transformers import AutoTokenizer, AutoModelForCausalLM
+import gradio as gr
+
+tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen-350M-mono")
+model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-mono")
+
+# text = "create a function recieve two arguments that return sum as a result"
+example_text = [ 'create a function to calculate the n!', "create a function recieve two arguments that return sum as a result"]
+
+def get_code(prompt):
+    input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+
+    generated_ids = model.generate(input_ids, max_length=128)
+    return tokenizer.decode(generated_ids[0], skip_special_tokens=True)
+
+demo = gr.Blocks()
+
+with demo:
+    gr.Markdown(
+        "## This Demo will generate python code only upto 128 tokens "
+    )
+    with gr.Row():
+        inputs = gr.Textbox(label='Prompt for generating code', lines=5)
+        outputs = gr.Textbox(label='Python Code', lines=10)
+    b1 = gr.Button('Generate Code')
+    gr.Examples(examples=example_text, inputs= inputs, outputs= outputs)
+
+    b1.click(fn = get_code,inputs= inputs, outputs= outputs )
+demo.launch()

requirements.txt

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+gradio
+transformers
+torch