Text Classification
Transformers
PyTorch
Romanian
vgcn
offensive language
graph neural networks
gnn
custom_code
Instructions to use andyP/ro-offense-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andyP/ro-offense-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="andyP/ro-offense-model", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("andyP/ro-offense-model", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd474b365076d091018a4b8d27aeea3fab1204ba518d56bf786b67ef5630cf4e
- Size of remote file:
- 482 MB
- SHA256:
- 2dd4760540bf1667e77b45ab271e0a87376a97ecb0ea7ab669391e45a5606820
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