Feature Extraction
sentence-transformers
ONNX
qwen3
embeddings
vespa
custom_code
text-embeddings-inference
Instructions to use thomasht86/voyage-4-nano-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thomasht86/voyage-4-nano-ONNX with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thomasht86/voyage-4-nano-ONNX", 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
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