Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use HelgeKn/Swag-multi-class-8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use HelgeKn/Swag-multi-class-8 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("HelgeKn/Swag-multi-class-8") - sentence-transformers
How to use HelgeKn/Swag-multi-class-8 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HelgeKn/Swag-multi-class-8") 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:
- 6fddda7810f255c4e429799b775ba052f9ba1f1dfe2642af097b45d5ea2f34ef
- Size of remote file:
- 438 MB
- SHA256:
- cc7287d62faf553bdf8bedf59124354ea8328bfbcc40968cc297c32f465c672a
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