Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use sleepinghdd/roberta-base-klue-ynat-classification-assignment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sleepinghdd/roberta-base-klue-ynat-classification-assignment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sleepinghdd/roberta-base-klue-ynat-classification-assignment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sleepinghdd/roberta-base-klue-ynat-classification-assignment") model = AutoModelForSequenceClassification.from_pretrained("sleepinghdd/roberta-base-klue-ynat-classification-assignment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2655838743b23dd9a1a745bf08aef9ffd7e46b38994c5c0e50cb98d18772c8d
- Size of remote file:
- 5.78 kB
- SHA256:
- b05946b7515b080efbc084248a2a3723fddf5a71aebc2139275be774ea9344f5
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