Instructions to use dss107/new_mp_base6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dss107/new_mp_base6 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dss107/new_mp_base6") 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/new_mp_base6 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("dss107/new_mp_base6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cee62a365c8bd301b693a495963b90d1bfdaf9b03cced3c9dceeca5dd492cbf0
- Size of remote file:
- 438 MB
- SHA256:
- 5316f010a546346f4cc5cb15ce525749e25e05ce7c51a951684421126a7a50c0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.