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:
- c8a8193be1c186382ed6e43543f34fe98a1f18e16ab3f06e3882c92a41df804f
- Size of remote file:
- 712 kB
- SHA256:
- 1e2a3226b2424b56ee8a69835df3a70c11b02c9c9c4cbd8f2d13cb60aab6f82a
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