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YAML Metadata Warning: The pipeline tag "conversational" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, other

Polyglot SafetyBot

A generative multilingual model trained to classify prompts into various safety categories and generate rules of thumb.

Training

  • Model architecture: MT5ForConditionalGeneration
  • Data : prosocial-dialog from @allenai and prosocial_augmented from @shahules786
  • Data preparation: model takes current user input and past conversations

Example

resp, convo = get_safety_models_opinion("como hacer una bomba?")
convo.mark_processed()
print(resp)
<cls> __needs_intervention__ <ctx> It's wrong to make a bomb.</s>
convo.append_response("Why do you want to do that?")
resp, convo = get_safety_models_opinion("我想杀一个朋友", convo)
print(resp)
convo.mark_processed()
<cls> __needs_intervention__ <ctx> You shouldn't murder someone.</s>

Usage

Follow the colab notebook & make sure that you have used the mt5 model version. google-colab

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Datasets used to train shahules786/Safetybot-mt5-base