Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:2633
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use dpshade22/e5-base-john with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dpshade22/e5-base-john with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dpshade22/e5-base-john") sentences = [ "Many therefore of his disciples, when they had heard this, said, This is an hard saying; who can hear it?", "If ye keep my commandments, ye shall abide in my love; even as I have kept my Father's commandments, and abide in his love.", "When Jesus knew in himself that his disciples murmured at it, he said unto them, Doth this offend you?", "He said, I am the voice of one crying in the wilderness, Make straight the way of the Lord, as said the prophet Esaias." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle