Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use Corran/CCRO2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Corran/CCRO2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Corran/CCRO2") - sentence-transformers
How to use Corran/CCRO2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Corran/CCRO2", trust_remote_code=True) 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:
- 5589885ea158a243d7ddfcbe03a3e8f102794f4b1cbc8344abbfe7837af6cb55
- Size of remote file:
- 549 MB
- SHA256:
- 2ac8ea871a491c0499c2c8b1292dced0f36e6b397f44e3819083551131586310
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