Instructions to use fhamborg/newsframes-aff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use fhamborg/newsframes-aff with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fhamborg/newsframes-aff") 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] - setfit
How to use fhamborg/newsframes-aff with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fhamborg/newsframes-aff") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73814944f49d86da8e53598e061d874e60d27667418e44edd0bc011347381b1f
- Size of remote file:
- 438 MB
- SHA256:
- 1579d5edbe6c6df9376e0f2a72741a2d28ae645bcdad8de769a2723880335c66
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.