Instructions to use nvidia/NV-Embed-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nvidia/NV-Embed-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nvidia/NV-Embed-v1", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Add the Sentence Transformers tag
#52
by tomaarsen HF Staff - opened
Hello!
This PR adds the Sentence Transformers tags, allowing people to find this model more easily when searching for embedding models under https://huggingface.co/models?library=sentence-transformers&sort=trending
Edit: Apologies, the automatic YAML metadata formatter in the web interface re-formatted some of the metadata. It shouldn't affect anything :)
- Tom Aarsen
nada5 changed pull request status to merged