- clarifai
- text-moderation
text-moderation-toxicity-mistral-7b
Workflow uses Mistral-7b Model with specified prompt template for Toxicity moderation that identify and filter out 'Toxic' sentiment includes aggression,
Notes
Toxicity Moderation
Workflow uses Mistral-7b Model with specified prompt template for Toxicity moderation that identify and filter out 'Toxic' sentiment includes aggression, hostility, or undue negativity and classifies the sentiment as 'Toxic', 'Suspicious', or 'Safe' based on the tone and content.
Text Moderation
Large Language Models (LLMs), like GPT (Generative Pretrained Transformer) variants, since they are pre-trained on diverse internet text, enabling them to understand context, nuance, and the subtleties of human language, to identify and filter out inappropriate or harmful content from digital platforms.
How to use the Toxicity Moderation workflow?
Using Clarifai SDK
Export your PAT as an environment variable. Then, import and initialize the API Client.
Find your PAT in your security settings.
export CLARIFAI_PAT={your personal access token}
Prediction with the workflow
from clarifai.client.workflow import Workflow
workflow_url = 'https://clarifai.com/{{user_id}}/text-moderation/workflows/text-moderation-toxicity-mistral-7b'
text = 'I love this movie and i would watch it again and again!'
prediction = Workflow(workflow_url).predict_by_bytes(text.encode(), input_type="text")
# Get workflow results
print(prediction.results[0].outputs[-1].data)
Using Workflow
To utilize the Text Moderation workflow, you can input text through the Blue Plus Try your own Input button and it will filter out 'Toxic' sentiment includes aggression, hostility, or undue negativity.
- Workflow IDtext-moderation-toxicity-mistral-7b
- DescriptionWorkflow uses Mistral-7b Model with specified prompt template for Toxicity moderation that identify and filter out 'Toxic' sentiment includes aggression, hostility, or undue negativity.
- Last UpdatedApr 09, 2024
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