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:
- 0ceaac4e4f934c87b8ce0765e204c5e604a58bc816218ab2cf32d37f31e25506
- Size of remote file:
- 36.9 kB
- SHA256:
- 54b8f87438f365f542c43a3e251e726a40c695f5d3c7011bb4c7b259df8222bc
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