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:
- 2048d7e939a4faa6705541dfc1d3a912841ae7b159b3c860ae6278132e174f2c
- Size of remote file:
- 4.03 kB
- SHA256:
- 9a40c1aca9f30e033838e2cd68ae0be6d0fbf819794751910b6d79c0b6fe742d
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