Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:262023
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use dpshade22/hf-e5-bible-300 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dpshade22/hf-e5-bible-300 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dpshade22/hf-e5-bible-300") sentences = [ "query: Jesus and Mary", "passage: Later, knowing that everything had now been finished, and so that Scripture would be fulfilled, Jesus said, “I am thirsty.”", "passage: But a young man saw them and told Absalom. So the two of them left at once and went to the house of a man in Bahurim. He had a well in his courtyard, and they climbed down into it.", "passage: As he says in Hosea:\n“I will call them ‘my people’ who are not my people;\n and I will call her ‘my loved one’ who is not my loved one,”" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle