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Mastering Transformers

You're reading from   Mastering Transformers Build state-of-the-art models from scratch with advanced natural language processing techniques

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781801077651
Length 374 pages
Edition 1st Edition
Languages
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Authors (2):
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Savaş Yıldırım Savaş Yıldırım
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Savaş Yıldırım
Meysam Asgari- Chenaghlu Meysam Asgari- Chenaghlu
Author Profile Icon Meysam Asgari- Chenaghlu
Meysam Asgari- Chenaghlu
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Introduction – Recent Developments in the Field, Installations, and Hello World Applications
2. Chapter 1: From Bag-of-Words to the Transformer FREE CHAPTER 3. Chapter 2: A Hands-On Introduction to the Subject 4. Section 2: Transformer Models – From Autoencoding to Autoregressive Models
5. Chapter 3: Autoencoding Language Models 6. Chapter 4:Autoregressive and Other Language Models 7. Chapter 5: Fine-Tuning Language Models for Text Classification 8. Chapter 6: Fine-Tuning Language Models for Token Classification 9. Chapter 7: Text Representation 10. Section 3: Advanced Topics
11. Chapter 8: Working with Efficient Transformers 12. Chapter 9:Cross-Lingual and Multilingual Language Modeling 13. Chapter 10: Serving Transformer Models 14. Chapter 11: Attention Visualization and Experiment Tracking 15. Other Books You May Enjoy

Sharing models with the community

HuggingFace provides a very easy-to-use model-sharing mechanism:

  1. You can simply use the following cli tool to log in:
    Transformers-cli login
  2. After you've logged in using your own credentials, you can create a repository:
    Transformers-cli repo create a-fancy-model-name
  3. You can put any model name for the a-fancy-model-name parameter and then it is essential to make sure you have git-lfs:
    git lfs install

    Git LFS is a Git extension used for handling large files. HuggingFace pretrained models are usually large files that require extra libraries such as LFS to be handled by Git.

  4. Then you can clone the repository you have just created:
    git clone https://huggingface.co/username/a-fancy-model-name
  5. Afterward, you can add and remove from the repository as you like, and then, just like Git usage, you have to run the following command:
    git add . && git commit -m "Update from $USER"
    git push

Autoencoding models rely...

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