Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Corran/SciGenSetfit2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Corran/SciGenSetfit2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Corran/SciGenSetfit2") - sentence-transformers
How to use Corran/SciGenSetfit2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Corran/SciGenSetfit2") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3166df6a8398bd16f494890245a0156d81ec85ada17910b0c47c58c3f72dae08
- Size of remote file:
- 75.4 kB
- SHA256:
- 7e64694fc9f6f4206f0376da8dbcc8dafcf28de90cb1968623575fa434fb57f6
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