Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Saliltrehan7/setfit-bge-small-v1.5-sst2-8-shot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Saliltrehan7/setfit-bge-small-v1.5-sst2-8-shot with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Saliltrehan7/setfit-bge-small-v1.5-sst2-8-shot") - sentence-transformers
How to use Saliltrehan7/setfit-bge-small-v1.5-sst2-8-shot with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Saliltrehan7/setfit-bge-small-v1.5-sst2-8-shot") 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:
- 2d6d5998e9ca96e40b6b169a9a998b4d2376e4877c51b3d2af4234e3c58b5c3a
- Size of remote file:
- 3.94 kB
- SHA256:
- 3e8410d2c23657b5b318bf68f9f724cbf62e9b534aa512641bd077b9ecf9e8c0
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