Use a better model for asymmetric semantic search

- 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
This commit is contained in:
Debanjum Singh Solanky
2022-07-18 20:00:19 +04:00
parent 5e302dbcda
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#+end_src
** Acknowledgments
- [[https://huggingface.co/sentence-transformers/msmarco-MiniLM-L-6-v3][MiniLM Model]] for Asymmetric Text Search. See [[https://www.sbert.net/examples/applications/retrieve_rerank/README.html][SBert Documentation]]
- [[https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1][MiniLM Model]] for Asymmetric Text Search. See [[https://www.sbert.net/examples/applications/retrieve_rerank/README.html][SBert Documentation]]
- [[https://github.com/openai/CLIP][OpenAI CLIP Model]] for Image Search. See [[https://www.sbert.net/examples/applications/image-search/README.html][SBert Documentation]]
- Charles Cave for [[http://members.optusnet.com.au/~charles57/GTD/orgnode.html][OrgNode Parser]]