# RetriBERT ## Overview The RetriBERT model was proposed in the blog post [Explain Anything Like I'm Five: A Model for Open Domain Long Form Question Answering](https://yjernite.github.io/lfqa.html). RetriBERT is a small model that uses either a single or pair 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 be found [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