How to building the index for the generated embeddings?

[linzhu1967]

Thanks for publishing the code of this important work.

I just follow the README to train the SLIM model on msmarco dataset again.
After generating the embeddings, I want to build an index on them but I don't no the details.
I try to find the instructions in pyserini, but the step about building index is omitted.
I really want to know how to build the index. I would appreciate your help.

I look forward to hearing from you.

[alexlimh]

Hi, you can create Lucene indexes using the following command:

python -m pyserini.index.lucene \
  --collection JsonVectorCollection \
  --input embeddings/doc \
  --index index_path \
  --generator DefaultLuceneDocumentGenerator \
  --threads 48 \
  --impact --pretokenized

[linzhu1967]

Thank you very much! I'll try it right away.