Several demos are available for people to play with our pre-trained SimCSE.
We provide a simple Web demo based on
flask to show how SimCSE can be directly used for information retrieval. The code is based on
DensePhrases'
repo and
demo (a lot of thanks to the authors of DensePhrases). To run this flask demo locally, make sure the SimCSE inference interfaces are setup:
1git clone https://github.com/princeton-nlp/SimCSE
2cd SimCSE
3python 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 to speed up the retrieval process.
AK391 has provided a
Gradio Web Demo of SimCSE to show how the pre-trained models can predict the semantic similarity between two sentences.
