Instructions to use YakovElm/Qt10SetFitModel_clean_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/Qt10SetFitModel_clean_data with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/Qt10SetFitModel_clean_data") 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/Qt10SetFitModel_clean_data with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/Qt10SetFitModel_clean_data") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 911ff89d91119274a06e91c5f88cef6ea74f2c528950cb6b7e41ccb94b9feae9
- Size of remote file:
- 438 MB
- SHA256:
- 10f8d1db70403e79f836b5640115cc272bf540eac9da00a41273db1bc4c45018
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