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## Example Usage |
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This section demonstrates how to use the `XiaoZhang98/byT5-DRS` model with the Hugging Face Transformers library to process an example sentence. |
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```python |
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from transformers import AutoTokenizer, T5ForConditionalGeneration |
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# Initialize the tokenizer and model |
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tokenizer = AutoTokenizer.from_pretrained('XiaoZhang98/byT5-DRS', max_length=512) |
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model = T5ForConditionalGeneration.from_pretrained("XiaoZhang98/byT5-DRS") |
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# Example sentence |
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example = "I am a student." |
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# Tokenize and prepare the input |
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x = tokenizer(example, return_tensors='pt', padding=True, truncation=True, max_length=512)['input_ids'] |
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# Generate output |
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output = model.generate(x) |
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# Decode and print the output text |
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pred_text = tokenizer.decode(output[0], skip_special_tokens=True, clean_up_tokenization_spaces=False) |
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print(pred_text) |
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