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5 days ago | |
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.. | ||
benchmarking | 7 months ago | |
contrastive-image-text | 2 weeks ago | |
image-classification | 2 weeks ago | |
language-modeling | 1 week ago | |
language-modeling-tpu | 3 months ago | |
multiple-choice | 2 weeks ago | |
question-answering | 2 weeks ago | |
summarization | 2 weeks ago | |
text-classification | 2 weeks ago | |
token-classification | 1 month ago | |
translation | 2 weeks ago | |
README.md | 5 days ago | |
_tests_requirements.txt | 1 month ago | |
test_tensorflow_examples.py | 4 months ago |
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!
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!
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 |