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Finetune Llama 3.3, DeepSeek-R1 & Reasoning LLMs 2x faster with 70% less memory
Get started quickly with Next.js, Postgres, Stripe, and shadcn/ui.
Do you like Quick, Draw? Well what if you could train/predict doodles drawn inside Streamlit? Also draws lines, circles and boxes over background images for annotation.
Select a portrait, click to move the head around (please use your own space / GPU!)
Composable building blocks to build Llama Apps
This is a Phi Family of SLMs book for getting started with Phi Models. Phi a family of open sourced AI models developed by Microsoft. Phi models are the most capable and cost-effective small langua…
A curated list of articles and tutorials to start with and understand generative AI
Following emerging Large Language Model Operations (LLM Ops) best practices in the industry, you’ll learn all about the key technologies that enable Generative AI practitioners like you to leverage…
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
DevOps Roadmap for 2024. with learning resources
A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Machine Learning Engineering Open Book
Source code for Twitter's Recommendation Algorithm
public mise ( http://en.wikipedia.org/wiki/Mise_en_place )
😎 A curated list of awesome MLOps tools
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
📚Open Source Curriculum for CNCF Certification Courses
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
A simple guide to MLOps through ZenML and its various integrations.
An end-to-end implementation of intent prediction with Metaflow and other cool tools
Joining the modern data stack with the modern ML stack
I am trying to describe complex matters in simple doodles!
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)