How Qwen2.5-1M Works ?

[@Sunil-ez1hx]

Such a wonderful video, very well explained mam

[@arnavthakur5409]

Ma'am your videos are very very helpful. Your way of explaination is really exceptional

[@ambiliya]

Cant wait to see the applications of it

[@jynpogger]

Thank you so much my teacher 🙏❤️. I'm greatful

[@CodeWithAarohi]

Welcome 🙂

[@pifordtechnologiespvtltd5698]

Nice work

[@tripchowdhry6124]

exceptional explanation - you are the best Teacher

[@CodeWithAarohi]

Thank you! 😃

[@soravsingla8782]

Amazing video

[@mahendrakumargohil6384]

Excellent explanation!!

[@CodeWithAarohi]

Thanks!

[@INDIOBRAVOO]

Thanks!

[@CodeWithAarohi]

Welcome!

[@Ishaheennabi]

Thanks for this

[@CodeWithAarohi]

No problem

[@R4hul4112]

Mam please make playlist with projects on Agentic AI

[@cynicalsingh3487]

Could be useful for summarizing podcast by feeding transcription

[@CodeWithAarohi]

Absolutely!

[@유영재-c9c]

Looking at the graph, there isn't much difference in understanding between 32K and 256K when applying DCA to 1M, right?

[@CodeWithAarohi]

Good observation!

[@ma8695t]

Dear Aarohi,
There is one point that I have never seen in any videos of youtube regarding "open source" llms. In fact, no one has talked about the concept of open source or if it is open source then how we can see the structure/architecture of those open source llms. I hope you could help us to demonstrate it.

[@CodeWithAarohi]

That’s a really important point! To truly call an LLM 'open-source,' it should provide Model Weights , Training Code and Architecture Details. For Qwen2.5-1M, you can check its architecture and model weights on Hugging Face

[@ma8695t]

Dear Aarohi,
Thanks a lot for your reply. Would you mind teaching us how to see visually such an architecture for models like LLaMA, Deepseek, etc. I would appreciate you in advance.

[@nursami7842]

please make videos EffientDet for Object Detection custom dataset maam

[@CodeWithAarohi]

Noted!

[@tourajmokhtarpour]

nice ❤

[@CodeWithAarohi]

Thanks