Fine-Tune Llama 3.2 Vision Model with Healthcare Images in 8 mins!

Поделиться
HTML-код
  • Опубликовано: 23 ноя 2024

Комментарии • 10

  • @softwareengineer8923
    @softwareengineer8923 7 часов назад +1

    Such a useful content, thanks a lot for the video👍

  • @Shine-and-line
    @Shine-and-line 4 часа назад

    Very useful information, thanks. Can you please share the code?

  • @kishpop
    @kishpop 5 часов назад

    Thx mate. These are awesome. Might you be able to do a similar video for training not just the external LoRA model weights to the cloud but one for training it locally on device and saving the weights locally - potentially to be used with Ollama?

    • @kishpop
      @kishpop 4 часа назад

      Just to add I presume the Ollama route is probably not possible with your own local version right? Or is it?

  • @alexa1017
    @alexa1017 7 часов назад +2

    I am wondering about the ToS of Llama for healthcare.. (clearly, it is non-commercial use…)

    • @rousabout7578
      @rousabout7578 6 часов назад

      Top result on Google search. "If, on the Llama 3.2 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensee’s affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights."

    • @mik3lang3lo
      @mik3lang3lo 6 часов назад

      I was thinking the same thing

    • @rousabout7578
      @rousabout7578 5 часов назад

      Google 'Llama 3.2 licence'. It's fairly open.

  • @yotubecreators47
    @yotubecreators47 8 часов назад +2

    Any time I see Fine tuning I click like before watching the video we need more finetuning + CPT cont. pretraining etc..
    how to epxlain loss/validation charts & W/B

  • @robertjalanda
    @robertjalanda 8 часов назад

    Thanks for this video. Is there an example or dataset with a more broad usecase? Radiography is a bit niche