Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use be2be2/roberta-base-klue-ynat-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use be2be2/roberta-base-klue-ynat-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="be2be2/roberta-base-klue-ynat-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("be2be2/roberta-base-klue-ynat-classification") model = AutoModelForSequenceClassification.from_pretrained("be2be2/roberta-base-klue-ynat-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from be2be2/roberta-base-klue-ynat-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/be2be2/roberta-base-klue-ynat-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://be2be2/roberta-base-klue-ynat-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/be2be2/roberta-base-klue-ynat-classification/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 681db04ae85061307cf8f3b3dd36504794dd0e1ecb6a92270ef2c847aa83aa20
- Size of remote file:
- 5.43 kB
- SHA256:
- 38ff9fdf234aa2e99291a80d2fba31c6fa8c1323f31db471b6f9bcdbf48bf126
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