Sentence Similarity
sentence-transformers
Safetensors
English
gemma3_text
biblical-search
semantic-search
embeddinggemma
fine-tuned
text-embeddings-inference
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:
- e45388e19a2da924d8fe6f3ccc97d38a52eeadce73dfa28c8b62ea4eb1c88d47
- Size of remote file:
- 9.44 MB
- SHA256:
- e172f748696361d83b3b3d98c188ad3f4f01dcb8bb032a4436a4c218a8aa16b7
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