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Bias and Toxicity In Large Language Models (LLMs) and Machine Learning
WK 3 – 9/18: Bias and Toxicity The discussion on bias and toxicity (and setting safety rules by either human agency or secondary machine monitoring/constitutional AI) made me want to raise my p(doom) value based on three possibilities: 1.) Unintended human errors (programming mistakes in setting up rules).2.) Intended human errors (bad actors ignoring ethics […]
Labs for DATA 78000: Large Language Models and Chat GPT
Mondays 6:30p, Room 5417, CUNY Graduate Center, New York, NYInstructor: Michelle McSweeney, michelleamcsweeney.com Course Site: https://github.com/michellejm/LLMs-fall-23 Link to this post: https://tinyurl.com/46ykcr68 Prompt Engineering Lab – Stanton for 78000https://colab.research.google.com/drive/1qWsqeooxflEDoIw5kaTOu3iv7A2aC9zd Ngrams Lab – Stantonhttps://colab.research.google.com/drive/1HebbqSpe5WXT45j9Oh1y7vOfHk6RO_nw Word Vectors Lab – Stantonhttps://colab.research.google.com/drive/1B2Qy5AzfZEp_wF34yW4Z8S82lF6LtFbT Tokeninzation Lab – Stanton for 78000https://colab.research.google.com/drive/1YXfrKuSNtG1HuWTiQ_-Qh87ru276Bwuu BERT Sentiment Via Huggingface – Stanton for 78000https://colab.research.google.com/drive/1OXrTaE6Ot5CCdpjjIKnl5jE4Rp5CD9W5 Fine Tune LLaMa – […]
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