Sentence Similarity
sentence-transformers
Safetensors
English
nvomniembed
text
image
video
audio
vidore
multimodal-embedding
Text-to-Video retrieval
Text-to-Audio retrieval
Visual Document Retrieval
feature-extraction
custom_code
Instructions to use nvidia/omni-embed-nemotron-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nvidia/omni-embed-nemotron-3b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nvidia/omni-embed-nemotron-3b", trust_remote_code=True) 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
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Integrate with Sentence Transformers v5.4 (#3)
Oliver Holworthy- Integrate Sentence Transformers v5.4.0 (1d1c44256a2e4c735d76b6d952ad5e801335c7d3) - Move 'message_format' into 'modality_config' under 'message' -> 'format' (68bb46c528a453a88932eafde0b9fcf058ed2ebe)e0e93aa
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