Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use gehaustein/PolyQual-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use gehaustein/PolyQual-2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("gehaustein/PolyQual-2") - sentence-transformers
How to use gehaustein/PolyQual-2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gehaustein/PolyQual-2") 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:
- 40b3f118604b28a70b35889d8db91f691403aa929416addc378b0e6a182fe291
- Size of remote file:
- 7.01 kB
- SHA256:
- aaf9e9d1f607467b37c209ef0c370e8fb2b9005c300420861103e0db7f9ad399
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