quickai
detoxify
| quickai | detoxify | |
|---|---|---|
| 7 | 4 | |
| 162 | 837 | |
| - | 1.7% | |
| 3.7 | 6.2 | |
| 30 days ago | 21 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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quickai
- Show HN: QuickAI Version 2 Released
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QuickAI version 2 released!
I originally released QuickAI here. I am very excited to announce version 2 of QuickAI
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QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
GitHub: https://github.com/geekjr/quickai
- Show HN: Quickai – Quickly experiment with state-of-the-art ML models
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quickai - A Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
Yeah, totally agree. https://github.com/geekjr/quickai/blob/main/quickai/image_classification.py does really need some reworking. Dicts are the way to go. But once that's done, I think it could actually be a practical lib!
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?
gpt-neo_dungeon - Colab notebooks to run a basic AI Dungeon clone using gpt-neo-2.7B
kogpt - KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)
segyio - Fast Python library for SEGY files.
multi-label-sentiment-classifier - How to build a multi-label sentiment classifiers with Tez and PyTorch
YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.
mesh-transformer-jax - Model parallel transformers in JAX and Haiku
chappie.ai - Generalized AI to perform a multitude of tasks written in python3
cedille-ai - ✒️ Cedille is a large French language model (6B), released under an open-source license
Note - Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, CLIP, ViT, ConvNeXt, SwiftFormer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow.
finetune-gpt2xl - Guide: Finetune GPT2-XL (1.5 Billion Parameters) and finetune GPT-NEO (2.7 B) on a single GPU with Huggingface Transformers using DeepSpeed
happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
google-local-results-ai-server - A server code for serving BERT-based models for text classification. It is designed by SerpApi for heavy-load prototyping and production tasks, specifically for the implementation of the google-local-results-ai-parser gem.