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README.md

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+---
+license: mit
+language: en
+tags:
+  - text-classification
+  - toxicity
+  - moderation
+  - chat
+  - bert
+  - pytorch
+  - onnx
+datasets:
+  - dormlab/chat-corpus
+metrics:
+  - accuracy
+  - f1
+  - precision
+  - recall
+pipeline_tag: text-classification
+---
+
+# Toxic Chat Moderation
+
+Binary classifier for real-time chat moderation. Flags toxic, hateful, harassing,
+sexually explicit, and otherwise inappropriate messages in gaming and social chat.
+
+Based on  fine-tuned on 300K labeled chat messages.
+
+## Quick use
+
+
+
+## Performance
+
+| Metric | Score |
+|--------|-------|
+| Accuracy | 0.9768 |
+| F1 | 0.9768 |
+| Precision | 0.9643 |
+| Recall | 0.9897 |
+
+ONNX INT8 latency: ~1-3ms on Apple Silicon (CoreML/MPS).
+
+## Training
+
+- **Architecture**: bert-base-uncased (110M params), 2 labels (clean/toxic)
+- **Hardware**: Apple Silicon Mac Mini (MPS), single-node
+- **Data**: 153K messages (122,688 train / 15,336 val / 15,336 test)
+- **Framework**: PyTorch, HuggingFace Trainer
+- **Export**: ONNX dynamic INT8 quantization (105 MB)
+
+## Variants
+
+This repo provides two model formats:
+-  — full PyTorch weights for use with usage: transformers <command> [<args>]
+
+positional arguments:
+  {chat,convert,download,env,run,serve,add-new-model-like,add-fast-image-processor}
+                        transformers command helpers
+    convert             CLI tool to run convert model from original author
+                        checkpoints to Transformers PyTorch checkpoints.
+    run                 Run a pipeline through the CLI
+    serve               CLI tool to run inference requests through REST and
+                        GraphQL endpoints.
+
+options:
+  -h, --help            show this help message and exit
+-  — ONNX INT8 quantized for fast inference on CPU/CoreML
+
+## Label mapping
+
+| Label | Meaning |
+|--------|---------|
+| 0 | Clean — allow |
+| 1 | Toxic — block/flag |