Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:178
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use rezarahim/bge-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rezarahim/bge-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rezarahim/bge-finetuned") sentences = [ "What is the purpose of the company's share repurchase program?", " The potential risks and challenges include the possibility of not receiving a license, imposition of burdensome conditions, disadvantage against competitors, complicated and time-consuming management of licenses, harm to competitive position, and potential denial of licenses to significant customers.", " The purpose of the company's share repurchase program is to offset dilution from shares issued to employees.", " The filing dates mentioned in the document are March 11, 2019, September 14, 2020, March 18, 2022, and March 8, 2023." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K