Sentence Similarity
sentence-transformers
Safetensors
Korean
English
xlm-roberta
feature-extraction
Korean
financial-nlp
nmixx
multilingual
text-embeddings-inference
Instructions to use nmixx-fin/nmixx-bge-m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nmixx-fin/nmixx-bge-m3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nmixx-fin/nmixx-bge-m3") 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
- Xet hash:
- 2589f399e7ba021e441f2a56e41e4b97448757ca175bc9ae5be3a44f54330ec4
- Size of remote file:
- 5.37 kB
- SHA256:
- 53cfbb89b4fecb6c7b7c64435b0d7ac27d1d68df9d090a7b7cbdaa1f76f93e76
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