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

tests/conftest.py

@@ -20,7 +20,7 @@ def search_config(tmp_path_factory):
     )
 
     search_config.asymmetric = AsymmetricSearchConfig(
-        encoder = "sentence-transformers/msmarco-MiniLM-L-6-v3",
+        encoder = "sentence-transformers/multi-qa-MiniLM-L6-cos-v1",
         cross_encoder = "cross-encoder/ms-marco-MiniLM-L-6-v2",
         model_directory = model_dir
     )