multi-label-sentiment-classifier
detoxify
| multi-label-sentiment-classifier | detoxify | |
|---|---|---|
| 1 | 4 | |
| 17 | 837 | |
| - | 1.7% | |
| 1.8 | 6.2 | |
| about 3 years ago | 22 days ago | |
| Jupyter Notebook | Python | |
| MIT License | Apache License 2.0 |
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multi-label-sentiment-classifier
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Training a Multi-Label Emotion Classifier with Tez and PyTorch to detect +20 different emotions
code: https://github.com/ahmedbesbes/multi-label-sentiment-classifier
detoxify
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ML Discord Moderation Bot
I created a small discord moderation bot, src can be found at https://gist.github.com/KrautByte/975f404969f4de8f4147e1bb4f7b64cb using https://github.com/unitaryai/detoxify
- Cedille, the largest French language model , released in open source
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Show HN: Cedille, the largest French language model, released in open source
Yeah, this kind of toxic output sadly still can happen :-/
We have fully analyzed the training dataset (1128 GB) using Detoxify (https://github.com/unitaryai/detoxify) to filter out problematic content. But of course detecting toxicity is a tough challenge in itself, so this process is imperfect at best.
We are using the RealToxicityPrompt framework (https://realtoxicityprompts.apps.allenai.org/) to analyse how toxic our models are and to steer our efforts in this direction. This means we are generating thousands of completions and analysing them to see how "nasty" the model is. We plan to write more on this topic soon.
But yeah, this is definitely far from being a solved problem, and our model (as well as all large language models) should be handled with care.
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Implementing a toxicity detector in your chatbots
Detoxify is the result of three Kaggle competitions proposed to improve toxicity classifiers. Each had a different purpose within the toxicity classifiers context.
What are some alternatives?
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cedille-ai - ✒️ Cedille is a large French language model (6B), released under an open-source license
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