- The multi-qa-MiniLM-L6-cos-v1 is more extensively benchmarked[1]
- It has the right mix of model query speed, size and performance on benchmarks
- On hugging face it has way more downloads and likes than the msmarco model[2]
- On very preliminary evaluation of the model
- It doubles the encoding speed of all entries (down from ~8min to 4mins)
- It gave more entries that stay relevant to the query (3/5 vs 1/5 earlier)
[1]: https://www.sbert.net/docs/pretrained_models.html
[2]: https://huggingface.co/sentence-transformers
- Put test data for each content type into separate directories
- Makes config.yml for docker and local host consistent
- Prepending tests to /data in sample_config.yml makes application
run on local host using test data
- Allows mounting separate volume for each content type in docker-compose
- Ignore gitignore to only add tests content, not generated models or embeddings
