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-500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dpshade22/hf-e5-bible-500 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dpshade22/hf-e5-bible-500") sentences = [ "query: Heir meaning", "passage: This is what the Lord commands for Zelophehad’s daughters: They may marry anyone they please as long as they marry within their father’s tribal clan.", "passage: The second one married the widow, but he also died, leaving no child. It was the same with the third.", "passage: and because the Lord loved him, he sent word through Nathan the prophet to name him Jedidiah." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dpshade22/hf-e5-bible-500: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/dpshade22/hf-e5-bible-500/resolve/main/tokenizer.json
- Command line
-
hf download hf://dpshade22/hf-e5-bible-500/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/dpshade22/hf-e5-bible-500/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.