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.
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.
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
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.
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.
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
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. 🙏😀
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.
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.
Hello. Yes, I am making a separate video on similar topic. It will be uploaded soon. Stay tuned my friend.
Amazing. Great work👍
Thanks Milind
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.
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
Great summary!!
thank you sir ! Fantastic method of explanation
Hey buddy. Thanks a lot. 😀
Hey buddy. Thanks a lot
Thanks for sharing. It's very informative. Keep up with this work.
Thank you, Santosh, for watching the video.
this is really nice explaination!!!
Thanks a lot Ganesh 😃 🙏
Very nice and to the point video, thank you !!!
Hey thanks a lot Ajit 😃 🙏
thanks for the excellent, well-explained summary!
Thank you Kevin
Very nicely explained ❤👍
Informative content
Thanks for sharing this
Glad you liked it!
thanks a lot❤
You are most welcome 😃 Do check other videos too on AI on this channel.
This is good. Keep up the good work. 🙂
Thank you Saket, I will
Thanks for sharing
My pleasure
Well done!
Thanks David.
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.
Hello. I will definitely make a video on the same. Thanks a lot. 😀
Greate video!
Thanks a lot. Please do share it with your friends 😁
Informative 👍
Glad it was helpful and informative for you Aditya. Please do share it with your friends. More interesting videos will be uploaded soon
Can you create a tutorial on Longformer and the concepts/code used to adapt an LLM for larger token sizes?
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.
Excellent
Thanks a lot Suhail.
Great summary- would be good if you did an update
Sure. I will make an updated video comprising of all the possible model architectures
Superb 🎉
Hey thanks William
Kudos🎉
Thank you 😃
It seems it does not cover BERT in computer vision.
Yes you are right Chen Peter
there's some new important ones like the newer gpt Neo models, alpaca, llama, cereus, vicuna
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
Thx
Most welcome 😃 😊
Hello, how do I contact/ connect with you, with regards to a project?
Hello, please contact us via our email. datafuseanalytics@gmail.com
this sounds like copy pasted from online articles and just reading from them without extra info at all
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. 🙏😀
for the algo
Thank you
Nice overview
Hey Thanks a lot 😃
This is good. Keep up the good work. 🙂
Hey Thanks Saket