Instructions to use memoravox/paraphrase-multilingual-MiniLM-L12-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use memoravox/paraphrase-multilingual-MiniLM-L12-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("memoravox/paraphrase-multilingual-MiniLM-L12-v2") 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
paraphrase-multilingual-MiniLM-L12-v2 (ONNX, quantized)
A mirror of the two files Memoravox's semantic index resolves at runtime:
onnx/model_quantized.onnx and tokenizer.json. Held in the memoravox org so
the product does not depend on a third-party account for a file it needs on first
run.
Upstream: Xenova/paraphrase-multilingual-MiniLM-L12-v2, itself an ONNX export of sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 (Apache-2.0). No weights were modified.