Text Classification
Transformers
PyTorch
English
bert
BERTicelli
text classification
abusive language
hate speech
offensive language
Instructions to use patrickquick/BERTicelli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickquick/BERTicelli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="patrickquick/BERTicelli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("patrickquick/BERTicelli") model = AutoModelForSequenceClassification.from_pretrained("patrickquick/BERTicelli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2071d294865849b2d8d97625fafd788b874c6508e3d1b7975c7d3beb85af4ac
- Size of remote file:
- 433 MB
- SHA256:
- 50454bc6dcf87e94a3f876ecc4c5e64514237fbb509fd2192bbe175beee462ca
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