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I trained a 12M parameter LLM on my own ML framework using a Rust backend and CUDA kernels for flash attention, AdamW, and more. Wrote the full transformer architecture, and BPE tokenizer from scratch. The framework features: - Custom CUDA kernels (Flash Attention, fused LayerNorm, fused GELU) for 3x... increased throughput - Automatic WebGPU fallback for non-NVIDIA devices - TypeScript API with Rust compute backend - One npm install to get started, prebuilt binaries for every platform Try out the model for yourself: Built with Reese Chong. Check out the repos and blog if you want to learn more. Shoutout to Modal for the compute credits allowing me to train on 2 A100 GPUs without going broke cc sunny madra Gavinshow more

Aadi Kulshrestha

4,064 subscribers

829,709 次观看 • 6 个月前 •via X (Twitter)

教育科学技术

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55 条评论

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Everything is open source, and we wrote a thorough blog breaking down everything we did so you guys can learn. Repo: Blog:

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Test the LLM and view the probability distribution of next tokens. All running in the browser using our own framework.

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

As per @ClementDelangue's suggestion, I uploaded the model to HuggingFace. Feel free to check it out and run the model yourself:

clem 🤗 的头像

clem 🤗6 个月前

you should share the model on

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Will most definitely do 🔥

Gavin 的头像

Gavin6 个月前

Love it. Dm me?

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

For sure!

Sanjoy Das 的头像

Sanjoy Das6 个月前

Nice! Would love to get your take on cuTile Rust:

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Looks interesting, will play around with it a bit and share my thoughts 👀

Bryce, the CUDA Colonel 的头像

Bryce, the CUDA Colonel6 个月前

DM me if you wanna chat about Rust for GPU programming!

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Will definitely reach out, even before I got into AI I did a lot of GPU programming work related to game development and rendering 🔥

Taelin 的头像

Taelin6 个月前

cost?

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

I spent ~$100 CAD of my own money, but @modal gave me ~$400 free credits at a hackathon a while back. The total was $500 of cloud compute

stan p 的头像

stan p6 个月前

waterloo strikes again

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

have to live up to the name

Ken Wu 的头像

Ken Wu6 个月前

how did i get into the same school as this beast

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Lmaooo 🙈

Kenny Guo 的头像

Kenny Guo6 个月前

first principles 🫡

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Yessir 🔥

dnu 的头像

dnu6 个月前

respect. writing your own framework is one thing, getting a full train run to converge is the part that usually gets ugly. what broke first for you, kernels or optimizer math?

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

We had a lot of bugs with our CUDA kernels that had to be addressed before the training started to go well 😂

Yechan Do 的头像

Yechan Do6 个月前

This is so impressive. Can I use your work at my lecture for education purpose ?

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

@yechan_ai Yes of course, we’re honoured 🔥

Saurabh Kumar 的头像

Saurabh Kumar6 个月前

What are they feeding Waterloo undergrads

ayush 的头像

ayush6 个月前

my goats @_reesechong and @MankyDankyBanky this is insane

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

@_reesechong Ty bro 🙏

Xander Chin 的头像

Xander Chin6 个月前

fire

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Appreciate it, TinyTPU was a big inspo

ani 的头像

ani6 个月前

🐐

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

nah you inspired me fr

Ricky Tang 的头像

Ricky Tang6 个月前

this is crazy bro

alexine 🏴‍☠️ 的头像

alexine 🏴‍☠️6 个月前

very cool, great work!

EDITH 的头像

EDITH6 个月前

This is fucking great man!!!

Kaibo Huang 的头像

Kaibo Huang6 个月前

@lucashjin good stuff aadi🔥

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

@lucashjin Thanks Kaibo looking forward to Bear hacks

mikael haji 的头像

mikael haji6 个月前

very nice!

Aryan Dhawan 的头像

Aryan Dhawan6 个月前

Amazing

Akram Jamil 的头像

Akram Jamil6 个月前

@nicholaschen__ cracked

Benedict Kerres 的头像

Benedict Kerres6 个月前

Well done

Rhys Campbell 的头像

Rhys Campbell6 个月前

@hnshah Part time model builder, full time looksmaxxer

Freeman Jiang 的头像

Freeman Jiang6 个月前

good stuff

Moulik 的头像

Moulik6 个月前

holy cracked

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

thanks moulik!

NILAY1556 的头像

NILAY15566 个月前

It's been my dream for long time to do something like that , impressive work Happy for you guyz to see you got much recognize by big giants Just great

evan 的头像

evan6 个月前

nice work!!

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Thanks so much Evan!

Nikhil Sonti 的头像

Nikhil Sonti6 个月前

training a transformer from scratch used to be frontier lab work now random devs ship full implementations with custom CUDA kernels... Rust backends... BPE tokenizers built from zero as side projects what took entire teams 2 years ago is now weekend hobby territory the commodification speed is wild

Lucas Jin 的头像

Lucas Jin6 个月前

@imdonghakim w aadi

sanjay prasad hs 的头像

sanjay prasad hs6 个月前

Super cool stuff, man, super cool.

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Thanks man!

benkigera 的头像

benkigera6 个月前

Reminds me of what LLMs are doing under the hood.

Dev Shorya 的头像

Dev Shorya6 个月前

thats actually insane. most people talk about it, you actually built it. the rust + cuda combo is hard mode too

Ajith Bondili 的头像

Ajith Bondili6 个月前

@anirudhbv_ce W

1jmdev 的头像

1jmdev6 个月前

Please update the demo page so it caches the model on user device it is really cool but please cache it on user device

Aadi Kulshrestha 的头像

Aadi Kulshrestha6 个月前

Good point, will try to get this out soon!

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voxium

36,987 次观看 • 3 个月前

Finally, I'm done with the basics of backend engineering on the all-in-one resources to learn backend engineering I'm working on This basic section includes - Internet - HTTP - Servers - Web Dev fundamentals - Fundamentals of Operating Systems - A server-side language -> JavaScript | Go | Rust | Node - A framework -> Express | Nestjs | Django | Laravel | Spring Boot This is the boring part. Don't worry. We are getting into the fun part soon. Still working on it, updating it, Adding more, and making it better for you. Follow me. Retweet. Comment "Backend." I will DM you the PDF version when it's out. Enjoy the web version, and send in your feedback on how we can improve it for everyone.

Finally, I'm done with the basics of backend engineering on the all-in-one resources to learn backend engineering I'm working on This basic section includes - Internet - HTTP - Servers - Web Dev fundamentals - Fundamentals of Operating Systems - A server-side language -> JavaScript | Go | Rust | Node - A framework -> Express | Nestjs | Django | Laravel | Spring Boot This is the boring part. Don't worry. We are getting into the fun part soon. Still working on it, updating it, Adding more, and making it better for you. Follow me. Retweet. Comment "Backend." I will DM you the PDF version when it's out. Enjoy the web version, and send in your feedback on how we can improve it for everyone.

Solomon Eseme

92,216 次观看 • 3 年前

Basic Guide to Playing MOG A quick guide to help beginners get familiar with the game and start farming corn for a Yield Fields (🧑‍🌾,🧑‍🌾) whitelist spot. Shoutout to skarly for putting more attention on the MOG grind 👀 Support me if you want:

Basic Guide to Playing MOG A quick guide to help beginners get familiar with the game and start farming corn for a Yield Fields (🧑‍🌾,🧑‍🌾) whitelist spot. Shoutout to skarly for putting more attention on the MOG grind 👀 Support me if you want:

John Huỳnh

25,172 次观看 • 1 个月前

Compute has always been core to the Verne Robotics story. Getting there meant negotiating long, expensive contracts with big neoclouds, and projecting compute needs years into the future. Verne wasn't ready for that. Then came the Y Combinator cluster, built on Together AI. Verne trained a model 3x larger, on almost 100x more data. More data in, bigger foundation models out.

Compute has always been core to the Verne Robotics story. Getting there meant negotiating long, expensive contracts with big neoclouds, and projecting compute needs years into the future. Verne wasn't ready for that. Then came the Y Combinator cluster, built on Together AI. Verne trained a model 3x larger, on almost 100x more data. More data in, bigger foundation models out.

Together AI

21,649 次观看 • 2 个月前

YOUR PARENTS PAID FOR THE CUDA MOAT! The #1 contributor to the CUDA MOAT isn't the the developers at NVIDIA, but it is the millions of developers outside of NVIDIA that invent new algorithms for CUDA like Flash Attention. For most of them, it started with an GeForce gaming GPU. NVIDIA is the only companies that has an reasonable good developer stack on consumer grade GPUs. As people grow up beyond playing CSGO & League of Legends & Minecraft, they either become anime weeaboos or they start programming on their existing computer with has an GeForce GPU

YOUR PARENTS PAID FOR THE CUDA MOAT! The #1 contributor to the CUDA MOAT isn't the the developers at NVIDIA, but it is the millions of developers outside of NVIDIA that invent new algorithms for CUDA like Flash Attention. For most of them, it started with an GeForce gaming GPU. NVIDIA is the only companies that has an reasonable good developer stack on consumer grade GPUs. As people grow up beyond playing CSGO & League of Legends & Minecraft, they either become anime weeaboos or they start programming on their existing computer with has an GeForce GPU

SemiAnalysis

25,230 次观看 • 6 个月前