[[open-in-colab]]
This page shows the most frequent use-cases when using the library. The models available allow for many different
configurations and a great versatility in use-cases. The most simple ones are presented here, showcasing usage for
tasks such as question answering, sequence classification, named entity recognition and others.
These examples leverage auto-models, which are classes that will instantiate a model according to a given checkpoint,
automatically selecting the correct model architecture. Please check the [AutoModel] documentation
for more information. Feel free to modify the code to be more specific and adapt it to your specific use-case.
In order for a model to perform well on a task, it must be loaded from a checkpoint corresponding to that task. These
checkpoints are usually pre-trained on a large corpus of data and fine-tuned on a specific task. This means the
