Instructions to use dss107/mp_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dss107/mp_base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dss107/mp_base") 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] - setfit
How to use dss107/mp_base with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("dss107/mp_base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5294b8467717c80cc1d470a4b77f86897bb6a6b6ca3722c6caf6b6a139ed2b68
- Size of remote file:
- 7.15 kB
- SHA256:
- fdc69a4ff4ae359e8c1654763ffe1c7cbc466c18243584f3c94bd18e3ebaf822
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.