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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("azherali/CodeGenDetect-BERT_Classifier") model = AutoModelForSequenceClassification.from_pretrained("azherali/CodeGenDetect-BERT_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from azherali/CodeGenDetect-BERT_Classifier: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
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https://huggingface.co/azherali/CodeGenDetect-BERT_Classifier/resolve/18758446a06d0b0e211fb1b1a454bced6edbc010/tokenizer.json
- Command line
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hf download hf://azherali/CodeGenDetect-BERT_Classifier@18758446a06d0b0e211fb1b1a454bced6edbc010/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/azherali/CodeGenDetect-BERT_Classifier/resolve/18758446a06d0b0e211fb1b1a454bced6edbc010/tokenizer.json
711 kB
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