Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:100
loss:TripletLoss
text-embeddings-inference
Instructions to use DariaaaS/e5-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use DariaaaS/e5-fine-tuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DariaaaS/e5-fine-tuned") sentences = [ "What is the average household income in the city known as \"Danzig\"?", "the most bad aliases refer to MAX(COUNT(bad_alias));", "Greeneville is the city;", "average household income refers to avg_income_per_household; city known as \"Danzig\" refers to bad_alias = 'Danzig';" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K