Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
dataset_size:1K<n<10K
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use xiaofengzi/bge-base-financial-matryoshka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use xiaofengzi/bge-base-financial-matryoshka with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("xiaofengzi/bge-base-financial-matryoshka") sentences = [ "What is the Path to Pro program related to?", "What types of programs are developed to upskill manufacturing employees?", "What was the overall turnover rate at the company in fiscal year 2023?", "What was the net interest revenue of The Charles Schwab Corporation in 2023?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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