Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use lovishag0315/bwc-setfit-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use lovishag0315/bwc-setfit-classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("lovishag0315/bwc-setfit-classifier") - sentence-transformers
How to use lovishag0315/bwc-setfit-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lovishag0315/bwc-setfit-classifier") 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
Download model_head.pkl from lovishag0315/bwc-setfit-classifier: direct link, hf CLI and curl.
- Browser
- Download file 69.2 kB
-
https://huggingface.co/lovishag0315/bwc-setfit-classifier/resolve/main/model_head.pkl
- Command line
-
hf download hf://lovishag0315/bwc-setfit-classifier/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/lovishag0315/bwc-setfit-classifier/resolve/main/model_head.pkl
69.2 kB
- Xet hash:
- 35364860c5571d2fd7984ff5e96efd7feaee45d62d34f0d5eea52f0975ddf473
- Size of remote file:
- 69.2 kB
- SHA256:
- 41e5e7992d552986576436d58c0c7e4a3347466ca9c2e8e9a48296990c952a6a
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