NLP with LLMs: Working with Tokenizers in Hugging Face
Large Language Models (LLMs)
| Intermediate
- 15 videos | 2h 18m 25s
- Includes Assessment
- Earns a Badge
Hugging Face, a leading company in the field of artificial intelligence (AI), offers a comprehensive platform that enables developers and researchers to build, train, and deploy state-of-the-art machine learning (ML) models with a strong emphasis on open collaboration and community-driven development. In this course, you will discover the extensive libraries and tools Hugging Face offers, including the Transformers library, which provides access to a vast array of pre-trained models and datasets. Next, you will set up your working environment in Google Colab. You will also explore the critical components of the text preprocessing pipeline: normalizers and pre-tokenizers. Finally, you will master various tokenization techniques, including byte pair encoding (BPE), Wordpiece, and Unigram tokenization, which are essential for working with transformer models. Through hands-on exercises, you will build and train BPE and WordPiece tokenizers, configuring normalizers and pre-tokenizers to fine-tune these tokenization methods.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Provide an overview of the hugging face platform
Outline how tokenization works for transformer models
Work with the hugging face platform
Set up a colab notebook
Explore normalization and pre-tokenization
Perform byte pair encoding (bpe) and wordpiece tokenization
Set up a bpe tokenizer -
Implement bpe tokenization
Set up a wordpiece tokenizer
Implement wordpiece tokenization
Train a bpe tokenizer
Perform normalization and pre-tokenization with wordpiece
Train a wordpiece tokenizer
Summarize the key concepts covered in this course
IN THIS COURSE
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2m 10sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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12m 5sAfter completing this video, you will be able to provide an overview of the Hugging Face platform. FREE ACCESS
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3. Hugging Face Tokenizers11m 20sUpon completion of this video, you will be able to outline how tokenization works for transformer models. FREE ACCESS
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4. Exploring the Hugging Face Platform11m 34sDiscover how to work with the Hugging Face platform. FREE ACCESS
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5. Setting up the Colab Environment5m 38sLearn how to set up a Colab notebook. FREE ACCESS
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6. Normalizers and Pre-tokenizers8m 2sIn this video, we will explore normalization and pre-tokenization. FREE ACCESS
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7. Byte Pair Encoding (BPE), Wordpiece, and Unigram Tokenization10m 18sDuring this video, you will learn how to perform byte pair encoding (BPE) and WordPiece tokenization. FREE ACCESS
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8. Implementing Byte Pair Encoding Tokenization - I12m 2sFind out how to set up a BPE tokenizer. FREE ACCESS
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9. Implementing Byte Pair Encoding Tokenization - II11m 58sIn this video, discover how to implement BPE tokenization. FREE ACCESS
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10. Implementing Wordpiece Tokenization - I12m 12sLearn how to set up a WordPiece tokenizer. FREE ACCESS
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11. Implementing Wordpiece Tokenization - II9m 36sDiscover how to implement WordPiece tokenization. FREE ACCESS
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12. Building and Training a BPE Tokenizer11m 22sIn this video, find out how to train a BPE tokenizer. FREE ACCESS
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13. Configuring the Normalizer and Pre-tokenizer for Wordpiece Tokenization7m 30sIn this video, you will learn how to perform normalization and pre-tokenization with WordPiece. FREE ACCESS
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14. Building and Training a Wordpiece Tokenizer9m 31sDiscover how to train a WordPiece tokenizer. FREE ACCESS
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15. Course Summary3m 7sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
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