## Demo of SimCSE Several demos are available for people to play with our pre-trained SimCSE. ### Flask Demo
We provide a simple Web demo based on [flask](https://github.com/pallets/flask) to show how SimCSE can be directly used for information retrieval. The code is based on [DensePhrases](https://arxiv.org/abs/2012.12624)' [repo](https://github.com/princeton-nlp/DensePhrases) and [demo](http://densephrases.korea.ac.kr) (a lot of thanks to the authors of DensePhrases). To run this flask demo locally, make sure the SimCSE inference interfaces are setup: ```bash git clone https://github.com/princeton-nlp/SimCSE cd SimCSE python setup.py develop ``` Then you can use `run_demo_example.sh` to launch the demo. As a default setting, we build the index for 1000 sentences sampled from STS-B dataset. Feel free to build the index of your own corpora. You can also install [faiss](https://github.com/facebookresearch/faiss) to speed up the retrieval process. ### Gradio Demo [AK391](https://github.com/AK391) has provided a [Gradio Web Demo](https://gradio.app/g/AK391/SimCSE) of SimCSE to show how the pre-trained models can predict the semantic similarity between two sentences.