Text Classification
setfit
ONNX
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Northell/ros-classifiers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Northell/ros-classifiers with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Northell/ros-classifiers") - sentence-transformers
How to use Northell/ros-classifiers with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Northell/ros-classifiers") 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:
- 74be3102881c4c8b089d3c15fbb8f493c35eab4f2b4e2d3e796397f0301fbdb6
- Size of remote file:
- 133 MB
- SHA256:
- efa751a822b7eb0a7db5d0167b6e38ffd6ad1978e71de205d7c0efedcc18bf2a
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