Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:70323
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use dpshade22/e5-base-bible with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dpshade22/e5-base-bible with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dpshade22/e5-base-bible") sentences = [ "Prophecies of Ezekiel | participants: ezekiel_1237", "I would seek unto God, and unto God would I commit my cause:", "And he shall deliver their kings into thine hand, and thou shalt destroy their name from under heaven: there shall no man be able to stand before thee, until thou have destroyed them.", "And I will set my jealousy against thee, and they shall deal furiously with thee: they shall take away thy nose and thine ears; and thy remnant shall fall by the sword: they shall take thy sons and thy daughters; and thy residue shall be devoured by the fire." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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