Text Classification
Transformers
PyTorch
English
modernbert
encoder
decision-model
tool-routing
agentic
Instructions to use open-zzrl/kyo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use open-zzrl/kyo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="open-zzrl/kyo")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("open-zzrl/kyo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from open-zzrl/kyo: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/open-zzrl/kyo/resolve/main/tokenizer.json
- Command line
-
hf download hf://open-zzrl/kyo/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/open-zzrl/kyo/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 33cd89ff8b53fbb07f89aa282b3d5bd5f5d7de3a2cdeca8540ee80380a8d3c1c
- Size of remote file:
- 34.4 MB
- SHA256:
- 8bd47075711f75a143d1b78e01a41cc65c1c591b00d3cfeffc23db07adce1392
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