Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:1936
loss:OnlineContrastiveLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use srikarvar/fine_tuned_model_11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use srikarvar/fine_tuned_model_11 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("srikarvar/fine_tuned_model_11") sentences = [ "What are the symptoms of COVID-19?", "How to identify COVID-19?", "What is the process for booking a dinner table?", "It is not necessary to include specific fields in a financial report; nevertheless, it is beneficial to add pertinent financial metrics to help investors gauge the company's condition." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K