## 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](https://huggingface.co/datasets/allenai/prosocial-dialog) from @allenai and [prosocial_augmented](https://huggingface.co/datasets/shahules786/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](https://colab.research.google.com/drive/1E-FidSeT5X1_FwNaa4x15uPi64f9ne7M?usp=sharing)
{"tags": ["mt5", "safety"], "datasets": ["allenai/prosocial-dialog", "shahules786/prosocial_augmented"], "pipeline_tag": "conversational"}
transformers pytorch mt5 text2text-generation safety conversational dataset:allenai/prosocial-dialog dataset:shahules786/prosocial_augmented autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #mt5 #text2text-generation #safety #conversational #dataset-allenai/prosocial-dialog #dataset-shahules786/prosocial_augmented #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

## 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






## Usage

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

Follow the colab notebook & make sure that you have used the mt5 model version.
google-colab
TAGS
#transformers #pytorch #mt5 #text2text-generation #safety #conversational #dataset-allenai/prosocial-dialog #dataset-shahules786/prosocial_augmented #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ## 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 ## Usage

Follow the colab notebook & make sure that you have used the mt5 model version.
google-colab
TAGS
#transformers #pytorch #mt5 #text2text-generation #safety #conversational #dataset-allenai/prosocial-dialog #dataset-shahules786/prosocial_augmented #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
## 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## Usage

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