Text Classification
Transformers
Safetensors
modernbert
moderation
toxicity
jailbreak-detection
multi-label
text-embeddings-inference
Instructions to use opus-research/opus-moderation-4-fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opus-research/opus-moderation-4-fast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="opus-research/opus-moderation-4-fast")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("opus-research/opus-moderation-4-fast") model = AutoModelForSequenceClassification.from_pretrained("opus-research/opus-moderation-4-fast", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4887caf55cefa93b7d9d3ced25e3419aad624e374529ad39d2574baea22a6ed
- Size of remote file:
- 5.27 kB
- SHA256:
- 9424a9a61038157a813e152aa84c6e45b398e0b4567a85571d72e3103370ca11
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.