Lukman Jibril Aliyu

lukmanaj

7 24 34

https://lukmanaj.github.io/

AI & ML interests

AI in healthcare | NLP | Computer Vision

Organizations

reacted to burtenshaw's post with ❤️ about 1 year ago

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5,747

new smol course

If you’re building with or learning about post training AI models right now, we have a new FREE and CERTIFIED course.

🔗 Follow the org to join in

smol-course

The course builds on smol course v1 which was the fastest way to learn to train your custom AI models. It now has:

- A leaderboard for students to submit models to
- Certification based on exams and leaderboards
- Prizes based on Leaderboards
- Up to date content on TRL and SmolLM3
- Deep integration with the Hub’s compute for model training and evaluation

We will release chapters every few weeks, so you can follow the org to stay updated.

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reacted to m-ric's post with 👀 over 1 year ago

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𝐇𝐮𝐠𝐠𝐢𝐧𝐠 𝐅𝐚𝐜𝐞 𝐫𝐞𝐥𝐞𝐚𝐬𝐞𝐬 𝐏𝐢𝐜𝐨𝐭𝐫𝐨𝐧, 𝐚 𝐦𝐢𝐜𝐫𝐨𝐬𝐜𝐨𝐩𝐢𝐜 𝐥𝐢𝐛 𝐭𝐡𝐚𝐭 𝐬𝐨𝐥𝐯𝐞𝐬 𝐋𝐋𝐌 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝟒𝐃 𝐩𝐚𝐫𝐚𝐥𝐥𝐞𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 🥳

🕰️ Llama-3.1-405B took 39 million GPU-hours to train, i.e. about 4.5 thousand years.

👴🏻 If they had needed all this time, we would have GPU stories from the time of Pharaoh 𓂀: "Alas, Lord of Two Lands, the shipment of counting-stones arriving from Cathay was lost to pirates, this shall delay the building of your computing temple by many moons "

🛠️ But instead, they just parallelized the training on 24k H100s, which made it take just a few months.
This required parallelizing across 4 dimensions: data, tensor, context, pipeline.
And it is infamously hard to do, making for bloated code repos that hold together only by magic.

🤏 𝗕𝘂𝘁 𝗻𝗼𝘄 𝘄𝗲 𝗱𝗼𝗻'𝘁 𝗻𝗲𝗲𝗱 𝗵𝘂𝗴𝗲 𝗿𝗲𝗽𝗼𝘀 𝗮𝗻𝘆𝗺𝗼𝗿𝗲! Instead of building mega-training codes, Hugging Face colleagues cooked in the other direction, towards tiny 4D parallelism libs. A team has built Nanotron, already widely used in industry.
And now a team releases Picotron, a radical approach to code 4D Parallelism in just a few hundred lines of code, a real engineering prowess, making it much easier to understand what's actually happening!

⚡ 𝗜𝘁'𝘀 𝘁𝗶𝗻𝘆, 𝘆𝗲𝘁 𝗽𝗼𝘄𝗲𝗿𝗳𝘂𝗹:
Counting in MFU (Model FLOPs Utilization, how much the model actually uses all the compute potential), this lib reaches ~50% on SmolLM-1.7B model with 8 H100 GPUs, which is really close to what huge libs would reach. (Caution: the team is leading further benchmarks to verify this)

Go take a look 👉 https://github.com/huggingface/picotron/tree/main/picotron

1 reply

reacted to burtenshaw's post with 🤗 over 1 year ago

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Brand new MCP Course has units are out, and now it's getting REAL! We've collaborated with Anthropic to dive deep into production ready and autonomous agents using MCP

🔗 mcp-course

This is what the new material covers and includes:

- Use Claude Code to build an autonomous PR agent
- Integrate your agent with Slack and Github to integrate it with you Team
- Get certified on your use case and share with the community
- Build an autonomous PR cleanup agent on the Hugging Face hub and deploy it with spaces

The material goes deep into these problems and helps you to build applications that work. We’re super excited to see what you build with it.

posted an update over 1 year ago

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Having an incredible time at the Agents MCP Hackathon

The learning curve has been steep but absolutely rewarding - diving deep into Model Context Protocol (MCP), building intelligent agents, and exploring the latest in LLM capabilities. There's something magical about seeing these technologies come together in real-time applications.

Huge shoutout to the hackathon organizers and sponsors for providing generous API credits from top inference providers. It's removed all the barriers to experimentation and let us focus purely on innovation and creativity. This level of support really makes the difference between having an idea and actually bringing it to life.

The community energy here is infectious - collaborating with brilliant minds, sharing breakthroughs, and learning from each other's approaches. Whether you're debugging MCP connections at 2 AM or celebrating a successful agent deployment, there's always someone ready to help or celebrate with you.

Interested in joining or learning more? Check out the hackathon details here:

Agents-MCP-Hackathon
What a time to be building in AI! 🔥

posted an update over 1 year ago

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I am so happy to share to all that I’ve just completed the first unit of the new MCP course on Hugging Face and earned my certificate! The AI acceleration track is intense and fast-paced, but I’m doing my best to keep up. Excited for what’s ahead!

1 reply

replied to their post over 1 year ago

Oh okay.

replied to their post over 1 year ago

Are we talking about the same course? This is entirely free.

replied to their post over 1 year ago

You can find the course here

posted an update over 1 year ago

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I’m excited to share that I’ve completed the Hugging Face Agents Course and earned my certificate.

Over the past few months, I explored how to build intelligent, autonomous agents using cutting-edge tools like smolagents, LlamaIndex, and LangGraph. The course covered everything from the fundamentals of agents to advanced topics like fine-tuning for function-calling, observability, evaluation, and even agents in games.

Some key content included:

1. Introduction to AI Agents

2. Agentic RAG use cases

3. Multi-framework implementation: smolagents, LlamaIndex, and LangGraph

4. Building, testing, and certifying a complete agent project

This was a hands-on, practical experience that deepened my understanding of how to design reliable, tool-using LLM agents. Looking forward to leveraging these skills in real-world applications in healthcare, logistics, and beyond.

Many thanks to the Hugging Face team for putting this together.
Let’s build safe and useful agents!

7 replies

reacted to m-ric's post with 😔 over 1 year ago

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4,947

"𝟮𝟬𝟮𝟱 𝘄𝗶𝗹𝗹 𝗯𝗲 𝘁𝗵𝗲 𝘆𝗲𝗮𝗿 𝗼𝗳 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀": this statement has often been made, here are numbers to support it.

I've plotted the progress of AI agents on GAIA test set, and it seems they're headed to catch up with the human baseline in early 2026.

And that progress is still driven mostly by the improvement of base LLMs: progress would be even faster with fine-tuned agentic models.

replied to their post over 1 year ago

I just logged in with my Hugging Face account and took the quiz without any issues. It was straightforward. You might be experiencing a temporary site issue—perhaps try clearing your cache, using a different browser, or waiting a bit in case the site is overloaded with requests

posted an update over 1 year ago

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I am excited to share that I’ve successfully completed Unit 1: Foundations of Agents in the Hugging Face Agents Course.
Exploring the fundamentals of AI agents has been an insightful journey, and I’m looking forward to applying these concepts in real-world applications.
Big thanks to the Hugging Face team for this amazing learning opportunity! 🤗
Check out the course here: https://huggingface.co/learn/agents-course/

2 replies

reacted to its5Q's post with 👍 about 2 years ago

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Continuing my streak by releasing the Wikireading dataset: a large collection of scraped non-fiction books predominantly in Russian language.
its5Q/wikireading

Here's the highlights:
- ~7B tokens, or ~28B characters, making it a great candidate for use in pretraining
- Contains non-fiction works from many knowledge domains
- Includes both the original HTML and extracted text of book chapters

reacted to victor's post with 🔥 about 2 years ago

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🙋 Calling all Hugging Face users! We want to hear from YOU!

What feature or improvement would make the biggest impact on Hugging Face?

Whether it's the Hub, better documentation, new integrations, or something completely different – we're all ears!

Your feedback shapes the future of Hugging Face. Drop your ideas in the comments below! 👇

191 replies

Lukman Jibril Aliyu

AI & ML interests

Organizations

lukmanaj's activity