Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:6300
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use Nishanth7803/bge-base-finetuned-financial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Nishanth7803/bge-base-finetuned-financial with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Nishanth7803/bge-base-finetuned-financial") sentences = [ "FedEx supports the mental health and well-being of its employees and their household members by providing 24/7 confidential counseling services and frequently communicating with employees on how to access these resources, with an increased focus on mental health resources in recent years.", "What are some of the key elements that management considers when making critical accounting estimates for Garmin?", "How does FedEx support the mental health and well-being of its employees and their household members?", "What was AbbVie's strategy for achieving its financial performance in 2023?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K