Feature Extraction
sentence-transformers
PyTorch
mpnet
sentence-similarity
text-embeddings-inference
Instructions to use model-embeddings/multi-qa-mpnet-base-dot-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use model-embeddings/multi-qa-mpnet-base-dot-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("model-embeddings/multi-qa-mpnet-base-dot-v1") 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:
- 3c946d620cf954d3ba3d55ee70b98a1a49eaca2364679cae80212f832f0587dc
- Size of remote file:
- 438 MB
- SHA256:
- 9e1e76b7a067f72e49c7f571cd8e811f7a1567bec49f17e5eaaea899e7bc2c9e
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