Thanks for the suggestion @reveching , I have added it to the to-do list at #7 and I'll try to make it after I return from vacation

I'm also very interested in the feature or any links on its implementation, thanks!

Hi @6r1d , I have already some working functionality of this, but in another repo: https://github.com/vicgalle/zero-shot-api/blob/main/pipeline.py#L30 In the main.py from there I have some simple examples.

Basically it should work with any model from the transformers library (but I recommend using those from sentence-transformers or summarization models), as it just computes the embedding vector of each query and keys and then computes the cosine similarity between them.

Over the next few days I'll have it integrated and served from this API!

Amazing, thank you very much, @vicgalle !

Is GPT-j less appropriate for that because of its speed?

@vicgalle Is this available via the API now? Also is the API able to return embeddings?