Instructions to use azherali/CodeGenDetect-BERT_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use azherali/CodeGenDetect-BERT_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="azherali/CodeGenDetect-BERT_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("azherali/CodeGenDetect-BERT_Classifier") model = AutoModelForSequenceClassification.from_pretrained("azherali/CodeGenDetect-BERT_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6dabc749db74212a6bac8c557e27201078b96fb152054a001fa234c1be93433
- Size of remote file:
- 438 MB
- SHA256:
- b01e88c32ba0ec1facde637c9b3a786e8c5cb1b308d5d73388aa03cdb60e07cd
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