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andlukyane.com | ||
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ehudreiter.com
Craig Thomson and I will present a paper at INLG on a methodology for evaluating the accuracy of generated texts, based on asking human annotators to mark up factual errors in a text. This is not cheap, but I think it is the most robust and reliable approach to measuring accuracy. |
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blog.reachsumit.com
Welcome to Sumit Kumar's Personal Blog! |
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saeedesmaili.com
I've been using conversational alpaca or sharegpt formats for fine-tuning LLMs with Axolotl , but it always felt unnecessary to limit the model on a conversational format when the use-case doesn't require so. I'm currently working on a project to classify pull requests in my company's code repositories. The model needs to look at the PR title, description, and code changes, then categorize the PR and explain its reasoning. I thought there must be a way to fine-tune these models with any format I see fitting this specific use-case, and sure there is: Template-free Axolotl |
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www.cambridge.org
Welcome to Cambridge Core |
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