Instructions to use erfansadraiye/ClassifyOffensiveTasks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erfansadraiye/ClassifyOffensiveTasks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="erfansadraiye/ClassifyOffensiveTasks")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("erfansadraiye/ClassifyOffensiveTasks") model = AutoModelForSequenceClassification.from_pretrained("erfansadraiye/ClassifyOffensiveTasks") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("erfansadraiye/ClassifyOffensiveTasks")
model = AutoModelForSequenceClassification.from_pretrained("erfansadraiye/ClassifyOffensiveTasks")Quick Links
Text Detoxification Classification
This is a classification model to detoxify text. It has been fine-tuned on OLID using the BERT model.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="erfansadraiye/ClassifyOffensiveTasks")