Text Classification
Transformers
Safetensors
modernbert
moderation
toxicity
jailbreak-detection
multi-label
text-embeddings-inference
Instructions to use opus-research/opus-moderation-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opus-research/opus-moderation-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="opus-research/opus-moderation-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("opus-research/opus-moderation-1") model = AutoModelForSequenceClassification.from_pretrained("opus-research/opus-moderation-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from opus-research/opus-moderation-1: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/opus-research/opus-moderation-1/resolve/main/tokenizer.json
- Command line
-
hf download hf://opus-research/opus-moderation-1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/opus-research/opus-moderation-1/resolve/main/tokenizer.json
3.58 MB
File too large to display, you can check the raw version instead.