Confused which Transformer Architecture to use? BERT, GPT-3, T5, Chat GPT? Encoder Decoder Explained

แชร์
ฝัง
  • เผยแพร่เมื่อ 26 ต.ค. 2024

ความคิดเห็น • 63

  • @datafuseanalytics
    @datafuseanalytics  ปีที่แล้ว +7

    In this video, I tried to explain all the major Transformer architectures. I have also explained the differences and training objective of each one of them. If you feel this video adds value in your life then please like, share and comment on this video and subscribe to this channel. If any suggestions and feedback then please drop in comment box.

  • @aurkom
    @aurkom ปีที่แล้ว +5

    It would have been awesome if all the models had the release year mentioned along with it as well. Helps to get a birds eye view of the timeline.

    • @datafuseanalytics
      @datafuseanalytics  ปีที่แล้ว

      Hello. Yes, I am making a separate video on similar topic. It will be uploaded soon. Stay tuned my friend.

  • @milindkubal2738
    @milindkubal2738 ปีที่แล้ว +5

    Amazing. Great work👍

  • @rembautimes8808
    @rembautimes8808 8 หลายเดือนก่อน +1

    Excellent video and I joined as a sub. Like this style of going thru the various architectures and the use case. Maybe you can also update it with GPT 4 since it’s new out there.

    • @datafuseanalytics
      @datafuseanalytics  7 หลายเดือนก่อน

      Thanks a lot for this amazing comment. I have uploaded the latest video using ChatGPT model - th-cam.com/video/MKHEaxdoqxA/w-d-xo.html
      Please go through it and feel free to comment

  • @snehotoshbanerjee1938
    @snehotoshbanerjee1938 4 หลายเดือนก่อน

    Great summary!!

  • @MJunaid-s6g
    @MJunaid-s6g 11 หลายเดือนก่อน +1

    thank you sir ! Fantastic method of explanation

  • @santoshpanigrahi5711
    @santoshpanigrahi5711 ปีที่แล้ว +2

    Thanks for sharing. It's very informative. Keep up with this work.

  • @ganeshkharad
    @ganeshkharad ปีที่แล้ว +1

    this is really nice explaination!!!

  • @ajitkumar15
    @ajitkumar15 ปีที่แล้ว +1

    Very nice and to the point video, thank you !!!

  • @kevon217
    @kevon217 ปีที่แล้ว +1

    thanks for the excellent, well-explained summary!

  • @hemantwani4757
    @hemantwani4757 5 หลายเดือนก่อน

    Very nicely explained ❤👍

  • @sagar3482
    @sagar3482 ปีที่แล้ว +1

    Informative content
    Thanks for sharing this

  • @amortalbeing
    @amortalbeing ปีที่แล้ว +1

    thanks a lot❤

    • @datafuseanalytics
      @datafuseanalytics  ปีที่แล้ว

      You are most welcome 😃 Do check other videos too on AI on this channel.

  • @SaketKumar-wy1wb
    @SaketKumar-wy1wb ปีที่แล้ว +1

    This is good. Keep up the good work. 🙂

  • @sanjaybhalke8032
    @sanjaybhalke8032 ปีที่แล้ว +2

    Thanks for sharing

  • @exxzxxe
    @exxzxxe ปีที่แล้ว +1

    Well done!

  • @falknfurter
    @falknfurter ปีที่แล้ว +1

    I just found this video and it's very good. I'm currently trying to understand when to use what type of model. Looking at Huggingface is just overwhelming. That's where this video jumps in and provides an excellent overview of the major models. I wish there would be a similiar video explaining the various pretraining objectives.

    • @datafuseanalytics
      @datafuseanalytics  ปีที่แล้ว

      Hello. I will definitely make a video on the same. Thanks a lot. 😀

  • @ahmedelsabagh6990
    @ahmedelsabagh6990 7 หลายเดือนก่อน +1

    Greate video!

    • @datafuseanalytics
      @datafuseanalytics  7 หลายเดือนก่อน

      Thanks a lot. Please do share it with your friends 😁

  • @adityakshirsagar1391
    @adityakshirsagar1391 ปีที่แล้ว +1

    Informative 👍

    • @datafuseanalytics
      @datafuseanalytics  ปีที่แล้ว

      Glad it was helpful and informative for you Aditya. Please do share it with your friends. More interesting videos will be uploaded soon

  • @d4munche3z
    @d4munche3z ปีที่แล้ว +1

    Can you create a tutorial on Longformer and the concepts/code used to adapt an LLM for larger token sizes?

    • @datafuseanalytics
      @datafuseanalytics  ปีที่แล้ว +1

      Hello David. I haven't made it yet. But I will definitely make one on Longformer etc which takes a whopping 4096 tokens as input. Thanks for your feedback.

  • @sarc007
    @sarc007 ปีที่แล้ว +1

    Excellent

  • @markfallu2389
    @markfallu2389 ปีที่แล้ว +1

    Great summary- would be good if you did an update

    • @datafuseanalytics
      @datafuseanalytics  ปีที่แล้ว

      Sure. I will make an updated video comprising of all the possible model architectures

  • @WillBeebe
    @WillBeebe ปีที่แล้ว +1

    Superb 🎉

  • @mhaya1
    @mhaya1 ปีที่แล้ว +1

    Kudos🎉

  • @chenpeter7428
    @chenpeter7428 ปีที่แล้ว +1

    It seems it does not cover BERT in computer vision.

  • @ianboyles2425
    @ianboyles2425 ปีที่แล้ว +1

    there's some new important ones like the newer gpt Neo models, alpaca, llama, cereus, vicuna

    • @datafuseanalytics
      @datafuseanalytics  ปีที่แล้ว

      Hello Ian. Yes. At the time of this session, these models weren't available. Thank you for your feedback. I will definitely make one video (part 2) which will encompass these models in a more simpler fashion

  • @tilkesh
    @tilkesh ปีที่แล้ว +1

    Thx

  • @projectbit2248
    @projectbit2248 ปีที่แล้ว

    Hello, how do I contact/ connect with you, with regards to a project?

    • @datafuseanalytics
      @datafuseanalytics  ปีที่แล้ว

      Hello, please contact us via our email. datafuseanalytics@gmail.com

  • @ko-Daegu
    @ko-Daegu ปีที่แล้ว +3

    this sounds like copy pasted from online articles and just reading from them without extra info at all

    • @datafuseanalytics
      @datafuseanalytics  ปีที่แล้ว

      Hey Ko-Jap. I referred multiple books for the same and then wrote the content in my language. But I did not refer to any online blogs or articles. Only books are the reference. But thank you for your valuable feedback. I will improve so that it doesn't sound as I am reading. 🙏😀

  • @yosup125
    @yosup125 10 หลายเดือนก่อน +1

    for the algo

  • @gregbugaj
    @gregbugaj ปีที่แล้ว

    Nice overview

  • @saketkr
    @saketkr ปีที่แล้ว +2

    This is good. Keep up the good work. 🙂