Instructions to use Morgan9803/roberta-base-klue-ynat-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Morgan9803/roberta-base-klue-ynat-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Morgan9803/roberta-base-klue-ynat-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Morgan9803/roberta-base-klue-ynat-classification") model = AutoModelForSequenceClassification.from_pretrained("Morgan9803/roberta-base-klue-ynat-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 902ac9dace310bd3752c3b441d04e5a15eacb8a3259a883b9eb6eca1d99d4bd0
- Size of remote file:
- 443 MB
- SHA256:
- e9c0ab9693378195bb3642678e9a6c180bd1e6c5f49eea1d3905980c9512c933
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