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Added example of how to pass text and padding in NLP processing. #397

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Added example of how to pass text and padding in NLP processing. #397

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19 changes: 19 additions & 0 deletions ffcv/tokenizer_example.py
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from transformers import AutoTokenizer

# Load a pre-trained tokenizer (BERT in this case)
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")

# Sample input text
text = ["Hello, how are you?", "I am learning NLP with Hugging Face!"]

# Tokenize text with padding
tokenized_output = tokenizer(
text,
padding=True, # Apply padding
truncation=True, # Truncate if needed
max_length=16, # Set max length
return_tensors="pt" # Return PyTorch tensors
)

# Print tokenized output
print(tokenized_output)