Text Classification
Transformers
Safetensors
English
bert
multi-label-classification
toxicity-detection
text-embeddings-inference
Instructions to use nmanish10/AI-DRIVEN_HARMFUL_LANGUAGE_DETECTOR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nmanish10/AI-DRIVEN_HARMFUL_LANGUAGE_DETECTOR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nmanish10/AI-DRIVEN_HARMFUL_LANGUAGE_DETECTOR")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nmanish10/AI-DRIVEN_HARMFUL_LANGUAGE_DETECTOR") model = AutoModelForSequenceClassification.from_pretrained("nmanish10/AI-DRIVEN_HARMFUL_LANGUAGE_DETECTOR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Model tree for nmanish10/AI-DRIVEN_HARMFUL_LANGUAGE_DETECTOR
Base model
unitary/toxic-bert