Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use HelgeKn/BEA2019-multi-class-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use HelgeKn/BEA2019-multi-class-4 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("HelgeKn/BEA2019-multi-class-4") - sentence-transformers
How to use HelgeKn/BEA2019-multi-class-4 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HelgeKn/BEA2019-multi-class-4") 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:
- 4bbef9c5439b4b3e737f21b01884889567fd5ce7cb3c9351e056410242f97fb1
- Size of remote file:
- 26.1 kB
- SHA256:
- 56eec723acfc91ef2ea01c5615a43f3d34a85d5a15627ac583ca5fbec40a4533
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