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Learn advanced tokenization techniques and pipeline internals in this comprehensive tutorial covering fast tokenizers, their performance advantages, and implementation details across PyTorch and TensorFlow frameworks. Explore the inner workings of token classification and question answering pipelines, understanding how they process text and generate predictions. Master the creation of custom tokenizers by examining normalization processes, pre-tokenization steps, and three major tokenization algorithms: Byte Pair Encoding (BPE), WordPiece, and Unigram tokenization. Gain hands-on experience building tokenizers from scratch and understand the technical foundations that make modern NLP models efficient and effective in processing natural language text.
