Stable Diffusion 3: Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

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  • เผยแพร่เมื่อ 10 พ.ย. 2024

ความคิดเห็น • 8

  • @TTTrouble
    @TTTrouble 7 หลายเดือนก่อน +3

    Man I took a break from getting into the weeds of the AI papers but I really appreciate that you’re still at it man, and it inspires me to jump back into the jungle. You’ve definitely been a fantastic source of knowledge and helped me break down some of this stuff in a really meaningful way. Keep up the great work!

  • @vladandronik5711
    @vladandronik5711 หลายเดือนก่อน

    Thanks for sharing! Struggled a bit with understanding flows, but you explained everything really nicely

  • @VisionTang
    @VisionTang หลายเดือนก่อน

    Thanks you a lot for sharing this! It helps me a lot

  • @kevinxu9562
    @kevinxu9562 7 หลายเดือนก่อน +1

    GOATED damn thank you so much for making a video on this! Timing is goated, just started going through your diffusion series as I'm trying to build a diffusion model!

  • @alexalex-lz8sg
    @alexalex-lz8sg 6 หลายเดือนก่อน

    Cool, what about latent adversarial diffusion distillation(LADD) video?

    • @gabrielmongaras
      @gabrielmongaras  6 หลายเดือนก่อน

      Oh yea that was a good paper. Lemmie maybe a video on that. This week seemed a bit lacking in terms of papers :/

  • @mathiasbang1999
    @mathiasbang1999 6 หลายเดือนก่อน

    Hey I was wondering if you could clarify something for me. You say that the [154; 4096] matrix holds the "fine grained" information, but when explaining the MM-DiT block setup Y is marked as fine grained information. It does seem to make more sense for the Y to be fine grained information in my opinion as it is post reduction information, however as I am not entirely sure I would love for you to maybe correct me on that :). Really appreciate the video! makes a lot of sense overall

  • @zeogod100
    @zeogod100 หลายเดือนก่อน

    I stopped watching when you named the image height "L", BLASPHAMY!