Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use faodl/setfit-paraphrase-mpnet-base-v2-5ClassesDesc-augmented-v02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use faodl/setfit-paraphrase-mpnet-base-v2-5ClassesDesc-augmented-v02 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("faodl/setfit-paraphrase-mpnet-base-v2-5ClassesDesc-augmented-v02") - sentence-transformers
How to use faodl/setfit-paraphrase-mpnet-base-v2-5ClassesDesc-augmented-v02 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("faodl/setfit-paraphrase-mpnet-base-v2-5ClassesDesc-augmented-v02") 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:
- 1e383a1580eaf3c042ced496ce81ee56a92f79ac27fe3f03b230452b17119547
- Size of remote file:
- 438 MB
- SHA256:
- b9a91b974f51b67ae3778c9a81720f1cb0e219d9cbf4245459e366bbea86583c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.