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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import gradio as grad |
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codegen_tkn = AutoTokenizer.from_pretrained("Salesforce/codegen-350M-mono") |
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mdl = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-mono") |
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def codegen(intent): |
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input_ids = codegen_tkn(intent, return_tensors="pt").input_ids |
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gen_ids = mdl.generate(input_ids, max_length=256) |
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response = codegen_tkn.decode(gen_ids[0], skip_special_tokens=True) |
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return response |
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output=grad.Textbox(lines=1, label="Generated Python Code", placeholder="") |
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inp=grad.Textbox(lines=1, label="Place your intent here") |
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grad.Interface(codegen, inputs=inp, outputs=output).launch() |
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