Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:3711
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use sistemas-upta/fine-tuned-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sistemas-upta/fine-tuned-st with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sistemas-upta/fine-tuned-st") sentences = [ "can excessive amounts of vitamin c cause me to have a miscarriage?", "what do indian politicians lack the most?", "how can vitamin c cause a miscarriage?", "what is the best programming language for hacking?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K