Feature Extraction
sentence-transformers
PyTorch
Core ML
ONNX
Safetensors
English
bert
sentence-similarity
mteb
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use jinaai/jina-embeddings-v2-small-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jinaai/jina-embeddings-v2-small-en with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jinaai/jina-embeddings-v2-small-en", 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
- Xet hash:
- f4519d24c65cf0407d5146c542b50594c3e694802aa7597d1eaf1e6b3b1a606d
- Size of remote file:
- 65.4 MB
- SHA256:
- c9a9a7ec012d01efd780474fbb65e25917f3a2aebdff84b5f87daa00f7e90b27
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