Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Shankhdhar/classifier_test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Shankhdhar/classifier_test_model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Shankhdhar/classifier_test_model") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use Shankhdhar/classifier_test_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Shankhdhar/classifier_test_model") 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/classifier_test_model: direct link, hf CLI and curl.
- Browser
- Download file 25.8 kB
-
https://huggingface.co/Shankhdhar/classifier_test_model/resolve/main/model_head.pkl
- Command line
-
hf download hf://Shankhdhar/classifier_test_model/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/Shankhdhar/classifier_test_model/resolve/main/model_head.pkl
25.8 kB
- Xet hash:
- 3d1f6c747bdbc3dbbd414203b04924c5db2e15dd2c9e9aeb2e9639d085f0467f
- Size of remote file:
- 25.8 kB
- SHA256:
- 064cfead1e021961e40e6c444837d275d4a72c59a0c8b642d9b42ab774d71c94
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