Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ashercn97/code-y-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use ashercn97/code-y-v1 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ashercn97/code-y-v1") - sentence-transformers
How to use ashercn97/code-y-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ashercn97/code-y-v1") 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:
- fa3d845fcac45b9410a00f6b57b6e2e6e3187f9a178a532b7a2dc9eb9c9242f4
- Size of remote file:
- 7.06 kB
- SHA256:
- 3bbc38c02f7a12e13822a2ca2b183a2f1952468a43e9ae43da72c41ba76e789d
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