Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use ashercn97/code-y-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use ashercn97/code-y-v2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ashercn97/code-y-v2") - sentence-transformers
How to use ashercn97/code-y-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ashercn97/code-y-v2") 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:
- ec200893e3f65c8d101d893b3604cfd91cd43eb3bda8a43f02a9ab0e2b056de1
- Size of remote file:
- 90.9 MB
- SHA256:
- e4b356b83b8701d5ac569dfe4ccea9b1aaea3c24e2ae370087438b48af25d3a1
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