Instructions to use sentence-transformers/paraphrase-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-mpnet-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/paraphrase-mpnet-base-v2") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use sentence-transformers/paraphrase-mpnet-base-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/paraphrase-mpnet-base-v2") model = AutoModel.from_pretrained("sentence-transformers/paraphrase-mpnet-base-v2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Request: DOI
Dear developers,
I am writing to request a Digital Object Identifier (DOI) for this HuggingFace repository (sentence-transformers/paraphrase-mpnet-base-v2).
This SentenceTransformer contains valuable resources related to my research and other works, and I plan to cite it in my paper. Having a DOI will enhance the visibility and accessibility of this work.
Thank you in advance for your attention to this matter. I look forward to receiving the DOI once it is assigned. 🤗
Sincerely,
Jiaxin Guo
FYI, there is the documentation on generating a DOI for models: https://huggingface.co/docs/hub/en/doi
The DOI has been generated, feel free to cite it: https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2?doi=true
Best of luck with your publication.
- Tom Aarsen