Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Finnish-actions/SetFit-FinBERT1-Avg-statement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Finnish-actions/SetFit-FinBERT1-Avg-statement with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Finnish-actions/SetFit-FinBERT1-Avg-statement") - sentence-transformers
How to use Finnish-actions/SetFit-FinBERT1-Avg-statement with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Finnish-actions/SetFit-FinBERT1-Avg-statement") 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:
- a90b2cb694bcabe6213749d2e2b409ec3b6e1c300fd1d5a3f3918a15543696fb
- Size of remote file:
- 7.01 kB
- SHA256:
- 80ab5af27aed3fb7c0e040a05483a158c833d87ce826b8c3b07e58ff263a0b8f
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