Text Classification
setfit
Safetensors
sentence-transformers
xlm-roberta
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use cnmoro/prompt-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use cnmoro/prompt-router with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("cnmoro/prompt-router") - sentence-transformers
How to use cnmoro/prompt-router with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cnmoro/prompt-router") 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
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name: Accuracy
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As of 28/07/2025, I instead of using this model, a simpler approach would be to just use one of these [Gliclass Models](https://huggingface.co/
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name: Accuracy
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As of 28/07/2025, I instead of using this model, a simpler approach would be to just use one of these [Gliclass Models](https://huggingface.co/cnmoro/gliclass-base-v3.0-onnx), matching the user's prompt against the prompts classes. But this model will remain here nonetheless.
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