Sentence Similarity
sentence-transformers
Safetensors
English
biblical-search
semantic-search
embeddinggemma
fine-tuned
Instructions to use dpshade22/embeddinggemma-scripture-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dpshade22/embeddinggemma-scripture-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dpshade22/embeddinggemma-scripture-v1") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68fbd5823822caec590fbf83be6ffda4ea81ad8ecb4c7c47099c825634931f7f
- Size of remote file:
- 1.21 GB
- SHA256:
- 55112959449bfe3eea485018f5ed06ac84b9ffe8b818911417520aa232638669
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