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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
def generate_doc(code_snippet):
model_name = "trained_model"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
inputs = tokenizer(code_snippet, return_tensors="pt")
outputs = model.generate(**inputs, max_length=128)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
if __name__ == "__main__":
print(generate_doc("def multiply(a, b): return a * b"))
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