Instructions to use YakovElm/IntelDAOS5SetFitModel_Train_balance_ratio_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/IntelDAOS5SetFitModel_Train_balance_ratio_3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/IntelDAOS5SetFitModel_Train_balance_ratio_3") 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 YakovElm/IntelDAOS5SetFitModel_Train_balance_ratio_3 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/IntelDAOS5SetFitModel_Train_balance_ratio_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 454dd4d1654f3f9d183e90d7303030e63aea8ee1c7a61396071bbaa563490c76
- Size of remote file:
- 6.99 kB
- SHA256:
- 444865bb1b7e08d9f93a562fd31a274d83c8fdccfb40338dc1d0199080fe2e44
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