Instructions to use YakovElm/Hyperledger15SetFitModel_Train_balance_ratio_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/Hyperledger15SetFitModel_Train_balance_ratio_1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/Hyperledger15SetFitModel_Train_balance_ratio_1") 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/Hyperledger15SetFitModel_Train_balance_ratio_1 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/Hyperledger15SetFitModel_Train_balance_ratio_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6e42e42ab076735095977dfb82a051fe4a19ca08744f8e926d65b98fb0b901f
- Size of remote file:
- 438 MB
- SHA256:
- 3787106b8522d939f7b9ad768a6ef00675eb3e8d33fa242776c57342fd7a1024
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