Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Eval Results
Instructions to use sentence-transformers/paraphrase-multilingual-mpnet-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/paraphrase-multilingual-mpnet-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/paraphrase-multilingual-mpnet-base-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] - Transformers
How to use sentence-transformers/paraphrase-multilingual-mpnet-base-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/paraphrase-multilingual-mpnet-base-v2") model = AutoModel.from_pretrained("sentence-transformers/paraphrase-multilingual-mpnet-base-v2") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
#13
by piyushsinghpasi - opened
Request to add chinese language in the README
Requesting to add zh (chinese) in the README for complete and accurate information.
Reference- Sentence transformer page has listed these languages: https://www.sbert.net/docs/sentence_transformer/pretrained_models.html#multilingual-models [zh-cn (chinese simplified) and zh-tw (chinese traditional)]
Also, I have tested this model, and it does support Chinese language.