Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use ITOCJ/CCRO2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use ITOCJ/CCRO2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ITOCJ/CCRO2") - sentence-transformers
How to use ITOCJ/CCRO2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ITOCJ/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:
- be2b08bcfb64e62c6caed85ea3d893176903cb66e3d1c58149db34d38af45a55
- Size of remote file:
- 56.8 kB
- SHA256:
- def5a2b21836fcf3f4fffbf1f7d674af5ccae2f6f92174ae4699a0182cc00b0f
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