Text Classification
ONNX
GGUF
sentence-transformers
multilingual
llama.cpp
qwen3
embedding
llama-cpp
jina-embeddings-v5
feature-extraction
mteb
vllm
text-embeddings-inference
Instructions to use TonitoMC/jina-embeddings-v5-text-small-classification-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use TonitoMC/jina-embeddings-v5-text-small-classification-onnx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("TonitoMC/jina-embeddings-v5-text-small-classification-onnx") 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:
- cb096516b5d9f86568d688cfbdfd63483fd8b1cdeee90ea0973ac6357de8a0d2
- Size of remote file:
- 11.4 MB
- SHA256:
- aed98cff73772352c260a48579f3b212cb2b06ce0553446799ebf0b5465b0673
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