Tokenization, Sequences, and Attention Masks with Hugging Face
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Covered the fundamental concepts of Transformer models, including tokenization and attention mechanisms. Learned how to use tokenizers to convert text into model-friendly tensors and explored the interaction between tokenizers and models for generating predictions. Reviewed important aspects such as input IDs and attention masks, building a foundation for navigating the Hugging Face documentation and implementing these models in machine learning tasks.