Instructions to use JminJ/kcElectra_base_Bad_Sentence_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JminJ/kcElectra_base_Bad_Sentence_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JminJ/kcElectra_base_Bad_Sentence_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JminJ/kcElectra_base_Bad_Sentence_Classifier") model = AutoModelForSequenceClassification.from_pretrained("JminJ/kcElectra_base_Bad_Sentence_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b3bb729b678f0494efeb20c815756a08ce0f035b3cf6ca7b8d38e6cf82c3764
- Size of remote file:
- 498 MB
- SHA256:
- fb20265acc61ec2014d4fdd05b2df336cb33fd40723a7a849505cdd25ca91627
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