Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Shankhdhar/jewellery_query_setfit_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Shankhdhar/jewellery_query_setfit_classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Shankhdhar/jewellery_query_setfit_classifier") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use Shankhdhar/jewellery_query_setfit_classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Shankhdhar/jewellery_query_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 Shankhdhar/jewellery_query_setfit_classifier: direct link, hf CLI and curl.
- Browser
- Download file 25.8 kB
-
https://huggingface.co/Shankhdhar/jewellery_query_setfit_classifier/resolve/main/model_head.pkl
- Command line
-
hf download hf://Shankhdhar/jewellery_query_setfit_classifier/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/Shankhdhar/jewellery_query_setfit_classifier/resolve/main/model_head.pkl
25.8 kB
- Xet hash:
- a39382c9d6f02000045061432b250bf54646751c29d8a7d748aa98b41ea032f3
- Size of remote file:
- 25.8 kB
- SHA256:
- f35e6601b6fc31203fb7fb7698a4679e65aa29287130a5450c65ac5a56bab741
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