Ordicio toxicity classifier (ONNX, int8)

An int8 ONNX export of textdetox/bert-multilingual-toxicity-classifier for on-device inference in the Ordicio apps (ONNX Runtime on Android / iOS, onnxruntime-web in browsers).

manifest.json: the current version, file hashes, tokenizer settings, labels and threshold.
v1/model.onnx: weights quantized to int8 (dynamic quantization), inputs input_ids, attention_mask, token_type_ids as int32 (cast to int64 inside the graph), output logits (index 0 neutral, 1 toxic).
v1/vocab.txt: the WordPiece vocabulary of the base model (cased, no lowercasing).

The int8 model agrees with the fp32 model on 98.5 % of decisions (3600 samples of textdetox/multilingual_toxicity_dataset in 12 languages). For accuracy per language, see the base model's card: German results are weak (F1 0.52).

The use restrictions of the openrail++ license of the base model apply to this export.

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Model tree for ordicio/toxicity-classifier

Base model

google-bert/bert-base-multilingual-cased

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textdetox/bert-multilingual-toxicity-classifier

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