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README.md
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For more information on my dataset, please see the included referenced dataset.
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# Hyperparameters
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MAX_SOURCE_LENGTH = 256 <br>
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For more information on my dataset, please see the included referenced dataset.
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You can test the model using this:
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```
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from transformers import T5ForConditionalGeneration, AutoTokenizer
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checkpoint = "Mir-2002/codet5p-google-style-docstrings"
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device = "cuda" # or CPU
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tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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model = T5ForConditionalGeneration.from_pretrained(checkpoint).to(device)
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input = """
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def calculate_sum(a, b):
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return a + b
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"""
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inputs = tokenizer.encode(input, return_tensors="pt").to(device)
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outputs = model.generate(inputs, max_length=128)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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# Calculate the sum of two numbers.
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# Args:
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# a (int): The first number.
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# b (int): The second number.
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```
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# Hyperparameters
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MAX_SOURCE_LENGTH = 256 <br>
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