detoxify and MAX-Toxic-Comment-Classifier
These are competitors offering alternative approaches to the same task—both detect toxic comments in text, but Detoxify provides pre-trained models for multiple toxicity subtypes with broader adoption, while MAX-Toxic-Comment-Classifier offers a containerized REST API service with IBM's Model Asset eXchange framework for different deployment preferences.
About detoxify
unitaryai/detoxify
Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers. For access to our API, please email us at contact@unitary.ai.
Provides three distinct model variants—`original`, `unbiased`, and `multilingual`—each optimized for different toxicity detection scenarios, with lightweight ALBERT-based alternatives for resource-constrained deployments. Leverages transformer-based architectures with bias-aware training on aggregated annotator judgments, supporting multi-label classification across toxicity subtypes (obscenity, threats, identity attacks, etc.) and identity mentions. Exposes predictions via a simple Python API returning per-category confidence scores and supports inference across seven languages with per-language performance metrics.
About MAX-Toxic-Comment-Classifier
IBM/MAX-Toxic-Comment-Classifier
Detect 6 types of toxicity in user comments.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work