I got my first job in a data science role as a fresher in 2018. And if you are from India you will know that back in 2018 it was a great…

I completed my college studies in 2018 and ChatGPT was launched in November, 2022. So obviously, I never get the chance to use ChatGPT…

Discover how to build reliable LLM applications by applying the E-Myth's systematic approach to automation. Learn why starting with human processes and incrementally automating tasks leads to more robust LLM applications. Perfect for startup founders and…

A comprehensive overview of lessons learned from the world's largest database of LLMOps case studies (457 entries as of January 2025), examining how companies implement and deploy LLMs in production. Through nine thematic blog posts covering everything from…

Colab notebook

This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full training stack of how the models are developed, along with mental models of how to think about their "psychology"…

As we’re still in the early days of building applications with foundation models, it’s normal to make mistakes. This is a quick note with examples of some of the most common pitfalls that I’ve seen, both from public case studies and from my personal experience.

Metromap for learning GenAI. Contribute to spraja08/GenAIMetroMap development by creating an account on GitHub.

Real Stories, Real Strategies: An Interviewer's Guide to What Actually Works

I received a PhD in Machine Learning from MIT in 2022.

6 months back, I started a project to teach “Hands on Large Language Models” to students, researchers and industry professionals.

The result is a mega-project with 30 videos covering everything about…

Insights from Cleric: Building an Autonomous AI SRE // MLOps Podcast #289 with Willem Pienaar, CTO & Co-Founder of Cleric.

// Abstract
In this MLOps Community Podcast episode, Willem Pienaar, CTO of Cleric, breaks down how they built an autonomous AI SRE…

A 3D animated visualization of an LLM with a walkthrough.

A mid in-depth technical review on how DeepSeek was developed

Introducing the Open Source LLMOps Stack based on LiteLLM and Langfuse which is well-integrated and can be easily self-hosted.

Colab notebook

Accuracy tells you how many times the ML model was correct overall. Precision is how good the model is at predicting a specific category. Recall tells you how many times the model was able to detect a specific category.

Org profile for Hugging Face Reasoning Course on Hugging Face, the AI community building the future.

The example-driven, practical walkthrough of Large Language Models and their growing list of related features, as a new entry to my general audience series on LLMs. In this more practical followup, I take you through the many ways I use LLMs in my own life.…

Speaker: Nouamane Tazi
https://huggingface.co/spaces/nanotron/ultrascale-playbook

(00:00:00): High Level Overview
(00:51:50): Data Parallelism
(1:32:11): Tensor Parallelism
(2:02:58) : Context Parallelism
(2:11:20): Pipeline Parallelism
(2:29:00): Expert…