LoveJesus/intertextual-dataset-chirho
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How to use LoveJesus/intertextual-embedder-chirho with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("LoveJesus/intertextual-embedder-chirho")
sentences = [
"That is a happy person",
"That is a happy dog",
"That is a very happy person",
"Today is a sunny day"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]For God so loved the world that he gave his only begotten Son, that whoever believes in him should not perish but have eternal life. - John 3:16
A sentence transformer fine-tuned for biblical verse similarity and cross-reference discovery. Given a verse text, it produces a 384-dimensional embedding that places semantically related verses close together in vector space.
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("LoveJesus/intertextual-embedder-chirho")
verses = [
"In the beginning God created the heaven and the earth.",
"In the beginning was the Word, and the Word was with God, and the Word was God.",
"And the children of Israel went into the midst of the sea upon the dry ground.",
]
embeddings = model.encode(verses)
# embeddings[0] will be closest to embeddings[1] (Gen 1:1 <-> John 1:1)
This model is part of the Intertextual Reference Network pipeline, paired with:
Built with love for Jesus by loveJesus.
Base model
microsoft/MiniLM-L12-H384-uncased