Text Classification
setfit
Safetensors
sentence-transformers
English
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use TinyModels/Setfit-banking-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use TinyModels/Setfit-banking-intent with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("TinyModels/Setfit-banking-intent") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use TinyModels/Setfit-banking-intent with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("TinyModels/Setfit-banking-intent") 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 TinyModels/Setfit-banking-intent: direct link, hf CLI and curl.
- Browser
- Download file 120 kB
-
https://huggingface.co/TinyModels/Setfit-banking-intent/resolve/main/model_head.pkl
- Command line
-
hf download hf://TinyModels/Setfit-banking-intent/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/TinyModels/Setfit-banking-intent/resolve/main/model_head.pkl
120 kB
- Xet hash:
- 4ab3ef4c1bb9e44a5a588cee6504abf2229662d1a9681dcc2e1cae38fba7344a
- Size of remote file:
- 120 kB
- SHA256:
- 6bf8498dc61c8c5b50323ddc1db946059b25288d0cb994f87964a91f4bdfd71e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.