RetriBERT
Source: transformers

# RetriBERT<Tip warning={true}>This model is in maintenance mode only, so we won't accept any new PRs changing its code.If you run into any issues running this model, please reinstall the last version that supported this model: v4.30.0.You can do so by running the following command: `pip install -U transformers==4.30.0`.</Tip>## OverviewThe RetriBERT model was proposed in the blog post [Explain Anything Like I'm Five: A Model for Open Domain Long FormQuestion Answering](https://yjernite.github.io/lfqa.html). RetriBERT is a small model that uses either a single orpair of BERT encoders with lower-dimension projection for dense semantic indexing of text.This model was contributed by [yjernite](https://huggingface.co/yjernite). Code to train and use the model can befound [here](https://github.com/huggingface/transformers/tree/main/examples/research-projects/distillation).## RetriBertConfig[[autodoc]] RetriBertConfig## RetriBertTokenizer[[autodoc]] RetriBertTokenizer## RetriBertTokenizerFast[[autodoc]] RetriBertTokenizerFast## RetriBertModel[[autodoc]] RetriBertModel    - forward