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zlm-v1-moderation-edge

**A 139M-parameter DeBERTa moderation model that flags unsafe English text and scores it on the 13 categories of the OpenAI moderation taxonomy, calibrated and small enough to run on the device (int8 ONNX, 185 MB).** For each input the model returns a binary **unsafe** verdict plus a calibrated score for each category: `hate`, `hate/threatening`, `harassment`, `harassment/threatening`, `self-harm`, `self-harm/intent`, `self-harm/instructions`, `sexual`, `sexual/minors`, `violence`, `violence/graphic`, `illicit`, `illicit/violent`. It runs locally with no network call. This is the exact bundle ZeroGPU runs on edge devices (browsers, Node.js / Docker workers, Android). It is laid out for transformers.js and also runs directly in onnxruntime.

**A 139M-parameter DeBERTa moderation model that flags unsafe English text and scores it on the 13 categories of the OpenAI moderation taxonomy, calibrated and small enough to run on the device (int8 ONNX, 185 MB).** For each input the model returns a binary **unsafe** verdict plus a calibrated score for each category: `hate`, `hate/threatening`, `harassment`, `harassment/threatening`, `self-harm`, `self-harm/intent`, `self-harm/instructions`, `sexual`, `sexual/minors`, `violence`, `violence/graphic`, `illicit`, `illicit/violent`. It runs locally with no network call. This is the exact bundle ZeroGPU runs on edge devices (browsers, Node.js / Docker workers, Android). It is laid out for transformers.js and also runs directly in onnxruntime.

Sources

huggingface.co ↗