transformers/examples/tensorflow
Matt 2e72bbab2c
Incorrect setting for num_beams in translation and summarization examples (#27519)
* Remove the torch main_process_first context manager from TF examples

* Correctly set num_beams=1 in our examples, and add a guard in GenerationConfig.validate()

* Update src/transformers/generation/configuration_utils.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
2023-11-15 18:18:54 +00:00
..
benchmarking Apply ruff flake8-comprehensions (#21694) 2023-02-22 09:14:54 +01:00
contrastive-image-text Dev version 2023-11-02 18:15:36 +01:00
image-classification Dev version 2023-11-02 18:15:36 +01:00
language-modeling Provide alternative when warning on use_auth_token (#27105) 2023-10-27 14:32:54 +02:00
language-modeling-tpu Add an option to reduce compile() console spam (#23938) 2023-06-02 15:28:52 +01:00
multiple-choice Incorrect setting for num_beams in translation and summarization examples (#27519) 2023-11-15 18:18:54 +00:00
question-answering Dev version 2023-11-02 18:15:36 +01:00
summarization Incorrect setting for num_beams in translation and summarization examples (#27519) 2023-11-15 18:18:54 +00:00
text-classification Dev version 2023-11-02 18:15:36 +01:00
token-classification Provide alternative when warning on use_auth_token (#27105) 2023-10-27 14:32:54 +02:00
translation Incorrect setting for num_beams in translation and summarization examples (#27519) 2023-11-15 18:18:54 +00:00
_tests_requirements.txt Pin Keras for now (#26904) 2023-10-19 14:39:31 +01:00
README.md Update README.md (#26198) 2023-09-19 00:02:50 +02:00
test_tensorflow_examples.py Proposed fix for TF example now running on safetensors. (#23208) 2023-05-09 13:04:27 -04:00

Examples

This folder contains actively maintained examples of the 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!