Use updated path to MiniLM bi-encoder model on hugging-face

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Debanjum Singh Solanky 2021-08-15 23:57:22 -07:00
parent 4839153086
commit 3b81fafa3e

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@ -14,9 +14,9 @@ import pathlib
def initialize_model(): def initialize_model():
"Initialize model for assymetric semantic search. That is, where query smaller than results" "Initialize model for assymetric semantic search. That is, where query smaller than results"
bi_encoder = SentenceTransformer('msmarco-MiniLM-L-6-v3') # The bi-encoder encodes all entries to use for semantic search bi_encoder = SentenceTransformer('sentence-transformers/msmarco-MiniLM-L-6-v3') # The bi-encoder encodes all entries to use for semantic search
top_k = 100 # Number of entries we want to retrieve with the bi-encoder top_k = 100 # Number of entries we want to retrieve with the bi-encoder
cross_encoder = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2') # The cross-encoder re-ranks the results to improve quality cross_encoder = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2') # The cross-encoder re-ranks the results to improve quality
return bi_encoder, cross_encoder, top_k return bi_encoder, cross_encoder, top_k