transformers/examples/tensorflow
Sylvain Gugger 6f79d26442
Update quality tooling for formatting (#21480)
* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

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benchmarking [NumPy] Remove references to deprecated NumPy type aliases (#21022) 2023-01-05 13:02:10 -05:00
image-classification Update quality tooling for formatting (#21480) 2023-02-06 18:10:56 -05:00
language-modeling Use return_tensors="np" instead of "tf" (#21266) 2023-01-24 13:37:49 +00:00
multiple-choice Update quality tooling for formatting (#21480) 2023-02-06 18:10:56 -05:00
question-answering Update quality tooling for formatting (#21480) 2023-02-06 18:10:56 -05:00
summarization Update quality tooling for formatting (#21480) 2023-02-06 18:10:56 -05:00
text-classification Update quality tooling for formatting (#21480) 2023-02-06 18:10:56 -05:00
token-classification Update quality tooling for formatting (#21480) 2023-02-06 18:10:56 -05:00
translation Update quality tooling for formatting (#21480) 2023-02-06 18:10:56 -05:00
_tests_requirements.txt Pin to the right version... 2022-11-18 07:12:55 -05:00
README.md Just re-reading the whole doc every couple of months 😬 (#18489) 2022-08-06 09:38:55 +02:00
test_tensorflow_examples.py Add TF image classification example script (#19956) 2023-02-01 19:09:36 +00:00

Examples

This folder contains actively maintained examples of use of 🤗 Transformers organized into different ML tasks. All examples in this folder are TensorFlow examples, and are written using native Keras rather than classes like TFTrainer, which we now consider deprecated. If you've previously only used 🤗 Transformers via TFTrainer, we highly recommend taking a look at the new style - we think it's a big improvement!

In addition, all scripts here now support the 🤗 Datasets library - you can grab entire datasets just by changing one command-line argument!

A note on code folding

Most of these examples have been formatted with #region blocks. In IDEs such as PyCharm and VSCode, these blocks mark named regions of code that can be folded for easier viewing. If you find any of these scripts overwhelming or difficult to follow, we highly recommend beginning with all regions folded and then examining regions one at a time!

The Big Table of Tasks

Here is the list of all our examples:

Task Example datasets
language-modeling WikiText-2
multiple-choice SWAG
question-answering SQuAD
summarization XSum
text-classification GLUE
token-classification CoNLL NER
translation WMT

Coming soon

  • Colab notebooks to easily run through these scripts!