Sentence Similarity
sentence-transformers
Safetensors
Korean
xlm-roberta
embeddings
retrieval
text-embeddings-inference
Instructions to use comhu/bge-m3-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use comhu/bge-m3-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("comhu/bge-m3-finetuned") 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] - Notebooks
- Google Colab
- Kaggle
bge-m3-finetuned
BAAI/bge-m3 ๋ฅผ ํ๊ตญ์ด ๊ฒ์(RAG) ์ฉ๋๋ก ํ์ธํ๋ํ ์๋ฒ ๋ฉ ๋ชจ๋ธ์
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์ฌ์ฉ๋ฒ
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("comhu/bge-m3-finetuned")
emb = model.encode(["๊ฒ์ ์ง์", "๋ฌธ์ ๋ด์ฉ"], normalize_embeddings=True)
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Model tree for comhu/bge-m3-finetuned
Base model
BAAI/bge-m3