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NLP Academy · Lesson

Tokenizing for Transformer Models

Subwords, padding, and attention masks.

Tokens Come First

Before a transformer can learn anything, your text must become numbers. That conversion job belongs to the tokenizer.

Match the Model

Always load the tokenizer that was trained with your model. A mismatched vocabulary produces garbage ids the model never saw.

from transformers import AutoTokenizer
tok = AutoTokenizer.from_pretrained("bert-base-uncased")

All lessons in this course

  1. The Transformers Library Tour
  2. Tokenizing for Transformer Models
  3. Fine-Tuning With the Trainer API
  4. Evaluating and Saving Your Model
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