Llama - EXPLAINED!

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Llama - EXPLAINED! 0:11:44

Llama - EXPLAINED!

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Комментарии
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Would you like to see more videos on Llama? Let me know. Have a wonderful day :)

CodeEmporium
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Yes please more deep dive into the code! Super valuable video because of that part.

jeswer
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The more i watch videos, the more i understand a subject, this is propably because i Can now see the subject in different angles or perspectives, now i have a better intuition of transformer architectures and i Can code it from scratch, thank you.

share
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Hey, thanks a lot for your videos. Your video - transformer attention is all you need helped me build an intuition back before transformers were really cool. It's lovely to see your video on llama, as I actively get to finetune llama on day to day basis :) Much love.

pipinstallyp
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Great video! Looking forward to deep dive into llama code

danar
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Clear, informative, well presented. Great video!

dollarscholar
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Thanks for the great video and a GREAT way of presenting data and showing the code!

steel-r_ua
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amazing work man. one of my favourite deep learning creators!

naevan
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Beautifully Explained. Thank you. Yes, I want to know more about its architecture too.

prasadraavi
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Would love a deep dive into stuff like LoRA and quantization (bitsandbytes library) as well. Perhaps, doing it from scratch in pytorch!

aurkom
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Thank you for such an insightful video. Would definitely love a deep-dive video on the architecture and code of LLama 2. Could you please also do an implementation of BERT or RoBERTa fine-tuning (the training process optimized via deepspeed) .
Thanks again!!

abhijitnayak
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yes. please. deep dive arch. and code walkthrough if possible.
Thanks a lot for the video. May gods blessing be with you.

gopalakrishna
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Commenting for the algorithm. Very well explained. You have a talent !

dinoscheidt
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Thank you so much for explaining brother!
Would be really great if you could give a code walkthrough video as well!

YashVerma-iilx
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Good explanation with proper understanding !

spydeyftw
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I have not implemented the code for decoder only so I have 3questions:

1. so it uses the triangular mask? I have heard from 2 sources which it does, but I dont get it, as we only feed inputs and not the outputs(unlike original transformer), how triangular mask on input data makes sense?

2. does why its called `decoder only`? the architecture seems much closer to encoder part of original transformer model, than its decoder part!! specially when the mask also not different than encoder of original.

3. is it autoregressive or still can be autoencoder to output the outputs in one pass?

popamaji
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Very informative!! Would be sick if you could dive deeper.

dikshyakasaju
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would you be intersted in making a guide of finetuning llamma2 or you thin kit is oversaturated?

naevan
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please make a video about how the generative feature and how the reinforcement learning is used in language models?

popamaji
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is this decoder with simplified form?!?!!?!? or its encoder with decoder mask?

popamaji