Instructions to use hyunkookim/roberta-base-klue-ynat-classification-using-pytorch-epoch_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyunkookim/roberta-base-klue-ynat-classification-using-pytorch-epoch_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hyunkookim/roberta-base-klue-ynat-classification-using-pytorch-epoch_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hyunkookim/roberta-base-klue-ynat-classification-using-pytorch-epoch_2") model = AutoModelForSequenceClassification.from_pretrained("hyunkookim/roberta-base-klue-ynat-classification-using-pytorch-epoch_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f9ce8899c8b6451336af80ccf5e03cfca40a52173f4b2b34572ec754403e511
- Size of remote file:
- 443 MB
- SHA256:
- 7f6fa01beba949e03bc25936cca5c9702e7de029497ceb37e3ffb0bafa32d662
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