bge-m3 distillations
Collection
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How to use altaidevorg/bge-m3-distill-6l with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("altaidevorg/bge-m3-distill-6l")
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]This is a sentence-transformers model distilled from BAAI/bge-m3 on the tr-sentences dataset. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. Refer to the blog post and the 8l variant for more information.
Base model
BAAI/bge-m3