Sentence Similarity
sentence-transformers
Safetensors
qwen2
feature-extraction
text-embeddings-inference
Instructions to use swankier/nomic-embed-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use swankier/nomic-embed-code with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("swankier/nomic-embed-code") 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
Commit History
-
update shared and index to allow for MLX conversion
Christopher Owen54a68c8
-
Update README.md
Verified signature1111402
-
Update README.md
Verified signature1ac68eb -
Update README.md
Verified signature5e79c62 -
Update README.md
Verified signaturee855ea0 -
Update README.md
Verified signature9de69ac -
Update README.md
Verified signaturef326ddf
-
Update config_sentence_transformers.json
Verified signatured0e6b4c -
Add new SentenceTransformer model
Verified signature9a04576 -
initial commit
Verified signature891adba