Instructions to use YakovElm/Hyperledger10SetFitModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/Hyperledger10SetFitModel with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/Hyperledger10SetFitModel") 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/Hyperledger10SetFitModel with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/Hyperledger10SetFitModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c600ee781935ebd0ba3930c8ab3d358589f63ad3d066bb0fc4edc07eec5f5aa
- Size of remote file:
- 438 MB
- SHA256:
- 5251e3c95bc9e23f6625e62a4dc281545c1c388eb8229d05579dade03bfd6bf8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.