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## Example Usage

This section demonstrates how to use the `XiaoZhang98/byT5-DRS` model with the Hugging Face Transformers library to process an example sentence.

```python
from transformers import AutoTokenizer, T5ForConditionalGeneration

# Initialize the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained('XiaoZhang98/byT5-DRS', max_length=512)
model = T5ForConditionalGeneration.from_pretrained("XiaoZhang98/byT5-DRS")

# Example sentence
example = "I am a student."

# Tokenize and prepare the input
x = tokenizer(example, return_tensors='pt', padding=True, truncation=True, max_length=512)['input_ids']

# Generate output
output = model.generate(x)

# Decode and print the output text
pred_text = tokenizer.decode(output[0], skip_special_tokens=True, clean_up_tokenization_spaces=False)
print(pred_text)