Instructions to use azherali/CodeGenDetect-Roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use azherali/CodeGenDetect-Roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="azherali/CodeGenDetect-Roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("azherali/CodeGenDetect-Roberta") model = AutoModelForSequenceClassification.from_pretrained("azherali/CodeGenDetect-Roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d32a6dd2b6a7fb130b849876eb1d2e5fbfec51bff8b0d4f5e00fbd52ca69e03
- Size of remote file:
- 499 MB
- SHA256:
- 60ce8f84510e77874c8b44762300a229ae68ea5ed13afd92eb7b61c3c5d6080a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.