Instructions to use azherali/CodeDetect-BERT-T2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use azherali/CodeDetect-BERT-T2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="azherali/CodeDetect-BERT-T2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("azherali/CodeDetect-BERT-T2") model = AutoModelForSequenceClassification.from_pretrained("azherali/CodeDetect-BERT-T2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 380b96b3365ff1d58e9f8bac759fd582f0b89a303470dfb6006a3942214ecdaa
- Size of remote file:
- 438 MB
- SHA256:
- f1a46695718b48a876c336a61d6bf1fd7091538c9e83716a3a82833b5ae08fca
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