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import transformers | |
def generate(idea): | |
# Load the code generation model | |
model_name = "PhiCo-D-Instruk" | |
model = transformers.AutoModelForCausalLM.from_pretrained(model_name) | |
tokenizer = transformers.AutoTokenizer.from_pretrained(model_name) | |
# Generate the code | |
input_text = f""" | |
# Idea: {idea} | |
# Code: | |
""" | |
input_ids = tokenizer.encode(input_text, return_tensors="pt") | |
output_sequences = model.generate( | |
input_ids=input_ids, | |
max_length=1024, | |
num_return_sequences=1, | |
no_repeat_ngram_size=2, | |
early_stopping=True, | |
) | |
generated_code = tokenizer.decode(output_sequences[0], skip_special_tokens=True) | |
return generated_code |