How to use from the
Use from the
sentence-transformers library
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("algoprog/ANCE-distilbert-ProCIS")

sentences = [
    "That is a happy person",
    "That is a happy dog",
    "That is a very happy person",
    "Today is a sunny day"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

ANCE ProCIS

This is a sentence-transformers model based on DistilBERT: It maps conversations and passages to dense embeddings for retrieval in the context of conversations. It's trained on the ProCIS dataset.

Citing & Authors

@article{Anonymous_2024_ProCIS,
  title   =  {ProCIS: A Benchmark for Proactive Retrieval in Conversations},
  author  =  {},
  journal =  {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year    =  {2024}
}
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