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app.py

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+from transformers import AutoTokenizer, AutoModelForCausalLM
+import gradio as grad
+codegen_tkn = AutoTokenizer.from_pretrained("Salesforce/codegen-350M-mono")
+mdl = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-mono")
+
+def codegen(intent):
+# give input as text which reflects intent of the program.
+     #text = " write a function which takes 2 numbers as input and returns the larger of the two"
+     input_ids = codegen_tkn(intent, return_tensors="pt").input_ids
+
+     gen_ids = mdl.generate(input_ids, max_length=128)
+     response = codegen_tkn.decode(gen_ids[0], skip_special_tokens=True)
+     return response
+
+output=grad.Textbox(lines=1, label="Generated Python Code", placeholder="")
+inp=grad.Textbox(lines=1, label="Place your intent here")
+grad.Interface(codegen, inputs=inp, outputs=output).launch()

requirements.txt

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+gradio
+git+https://github.com/huggingface/transformers.git
+torch
+transformers[sentencepiece]