Instructions to use AISE-TUDelft/extended-java-pointer-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AISE-TUDelft/extended-java-pointer-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AISE-TUDelft/extended-java-pointer-classifier") 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 AISE-TUDelft/extended-java-pointer-classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("AISE-TUDelft/extended-java-pointer-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0b3556206b9710a7a953830e6bae6e9c3a09ba33e02a3bf3719b6744faba44a
- Size of remote file:
- 438 MB
- SHA256:
- 2157dec92859e62f90bd5a887570ba3e991f3ccbca23d513ce64153cff80f995
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.