Text Classification
Transformers
PyTorch
Romanian
bert
hate speech
offensive language
romanian
classification
nlp
Eval Results (legacy)
text-embeddings-inference
Instructions to use readerbench/ro-offense with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use readerbench/ro-offense with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="readerbench/ro-offense")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("readerbench/ro-offense") model = AutoModelForSequenceClassification.from_pretrained("readerbench/ro-offense") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4dbfba867fcb7aba36292377b14dfd2b624b372ee75d981df30aed846d572d0d
- Size of remote file:
- 460 MB
- SHA256:
- a47354669e9c3f3d15971ae87ee33670e6274dd9d16b7ba24c4f07cad9f32fd5
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