MMR Multiprocessing
- Dominant language
- Python
- Stars
- 4.2k
- Forks
- 385
- PR merge metrics
- No merged PRs in 30d
Description
Hi, I'm loving KeyBERT and using it for a project now. However, I'm noticing that performance is very slow at scale when using MMR. I'm observing that running the embedding model on GPU speeds things up, but it seems that the bottleneck is now MMR computation on CPU. Does KeyBERT natively support multiprocessing that?
My plan was to break this all out- start by computing my own n-grams, then embedding the n-grams and documents directly, and passing the embeddings to KeyBERT in a multiprocessing setup (i.e. map a huge list of embeddings to multiple processes of KeyBERT to perform the MMR). But before I go down that road, I just want to double check that this is not already supported natively in KeyBERT?
Contributor guide
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Research direction
The issue names no files, tests, or entry points. Start by locating KeyBERT's MMR execution path and checking whether multiprocessing is already documented or implemented; done means a clear support answer or a scoped change with tests identified.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100