Instructions to use TurkuNLP/web-register-classification-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TurkuNLP/web-register-classification-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TurkuNLP/web-register-classification-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TurkuNLP/web-register-classification-multilingual") model = AutoModelForSequenceClassification.from_pretrained("TurkuNLP/web-register-classification-multilingual") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a683567fa6c3ba67f1f53302b0b7b3dcd25795a79d0234e85ee9ab7c8811ad4a
- Size of remote file:
- 5.05 kB
- SHA256:
- ebf403c952a10b2c8536d4787b9c94e81a9be354ce8e46705c1ed18a2600a9d8
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