Text Classification
setfit
ONNX
attention-weights
context-compression
intent-classification
multilingual
Instructions to use naranor/SetFit-Multilingual-ONNX-Router-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use naranor/SetFit-Multilingual-ONNX-Router-V1 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("naranor/SetFit-Multilingual-ONNX-Router-V1") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from naranor/SetFit-Multilingual-ONNX-Router-V1: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/naranor/SetFit-Multilingual-ONNX-Router-V1/resolve/main/tokenizer.json
- Command line
-
hf download hf://naranor/SetFit-Multilingual-ONNX-Router-V1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/naranor/SetFit-Multilingual-ONNX-Router-V1/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 9a184b2b11046834b0cd331a6add8c60f316cd5fc20f545baf507182cfc22a21
- Size of remote file:
- 17.1 MB
- SHA256:
- 3a56def25aa40facc030ea8b0b87f3688e4b3c39eb8b45d5702b3a1300fe2a20
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