unicamp-dl/mmarco
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How to use andreaschari/bge-m3-lt-cafr with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("andreaschari/bge-m3-lt-cafr")
sentences = [
"The weather is lovely today.",
"It's so sunny outside!",
"He drove to the stadium."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]This is a BGE-M3 model post-trained on French translated to Catalan Queries and French Documents from MMARCO/v2.
This model was fine-tuned for the "Improving Low-Resource Retrieval Effectiveness using Zero-Shot Linguistic Similarity Transfer" ECIR2025 paper. The source code for the paper can be found here
Base model
BAAI/bge-m3