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 training_args.bin from azherali/CodeGenDetect-BERT_Classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/azherali/CodeGenDetect-BERT_Classifier/resolve/808cda86b47f95a9319f98eabb5ed207c075c9a0/training_args.bin
- Command line
-
hf download hf://azherali/CodeGenDetect-BERT_Classifier@808cda86b47f95a9319f98eabb5ed207c075c9a0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/azherali/CodeGenDetect-BERT_Classifier/resolve/808cda86b47f95a9319f98eabb5ed207c075c9a0/training_args.bin
5.18 kB
- Xet hash:
- e04c842996e248dcd5f0483bb7813d93521b521f47a69fa76eee140d40d6e6f9
- Size of remote file:
- 5.18 kB
- SHA256:
- d54cbc4d597c6e00be453e2761859d2546590f8bb967a231fdea502ac5eaccf7
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