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@@ -33,6 +33,33 @@ Raises:
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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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+ ```
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+ from transformers import T5ForConditionalGeneration, AutoTokenizer
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+
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+ checkpoint = "Mir-2002/codet5p-google-style-docstrings"
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+ device = "cuda" # or CPU
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+
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+ tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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+ model = T5ForConditionalGeneration.from_pretrained(checkpoint).to(device)
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+
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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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+
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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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+
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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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+ ```
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+
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  # Hyperparameters
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  MAX_SOURCE_LENGTH = 256 <br>