Text Classification
sentence-transformers
PyTorch
setfit
multilingual
xlm-roberta
text-embeddings-inference
Instructions to use uaritm/test_depres with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use uaritm/test_depres with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("uaritm/test_depres") 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 uaritm/test_depres with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("uaritm/test_depres") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3e6399d7256dd48dc87c0c10fa3c3ecf34ec6e75d3850a601d03c82a8b6062b
- Size of remote file:
- 1.11 GB
- SHA256:
- e771f765e005fc43a41d736df8a462739e345727f7363139ccb2d44677dc7fae
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