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Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
AI agents running research on single-GPU nanochat training automatically
ใๅจๆๅญฆๆทฑๅบฆๅญฆไน ใ๏ผ้ขๅไธญๆ่ฏป่ ใ่ฝ่ฟ่กใๅฏ่ฎจ่ฎบใไธญ่ฑๆ็่ขซ70ๅคไธชๅฝๅฎถ็500ๅคๆๅคงๅญฆ็จไบๆๅญฆใ
๐งโ๐ซ 60+ Implementations/tutorials of deep learning papers with side-by-side notes ๐; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gaโฆ
ChatDev 2.0: Dev All through LLM-powered Multi-Agent Collaboration
120+ interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
gpt-oss-120b and gpt-oss-20b are two open-weight language models by OpenAI
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Tensorflow2.0 ๐๐ is delicious, just eat it! ๐๐
A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
Example projects using the AWS CDK
๐100+ ๅๅ LLM / RL ๅ็ๅพ๐๏ผใๅคงๆจกๅ็ฎๆณใไฝ่ ๅทจ็ฎ๏ผ๐ฅ๏ผ100+ LLM/RL Algorithm Maps ๏ผ
๐ค ๐๐ฒ๐ฎ๐ฟ๐ป for ๐ณ๐ฟ๐ฒ๐ฒ how to ๐ฏ๐๐ถ๐น๐ฑ an end-to-end ๐ฝ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป-๐ฟ๐ฒ๐ฎ๐ฑ๐ ๐๐๐ & ๐ฅ๐๐ ๐๐๐๐๐ฒ๐บ using ๐๐๐ ๐ข๐ฝ๐ best practices: ~ ๐ด๐ฐ๐ถ๐ณ๐ค๐ฆ ๐ค๐ฐ๐ฅ๐ฆ + 12 ๐ฉ๐ข๐ฏ๐ฅ๐ด-๐ฐ๐ฏ ๐ญ๐ฆ๐ด๐ด๐ฐ๐ฏ๐ด
vLLMโs reference system for K8S-native cluster-wide deployment with community-driven performance optimization
Code and model for the paper "Improving Language Understanding by Generative Pre-Training"
Sample code for a simple web chat experience through Azure OpenAI, including Azure OpenAI On Your Data.
Master the fundamentals of machine learning, deep learning, and mathematical optimization by building key concepts and models from scratch using Python.
Several simple examples for popular neural network toolkits calling custom CUDA operators.
Programmatically extract data and apply schemas to unstructured documents across text-based and multi-modal content using Azure AI Foundry, Azure OpenAI, Azure AI Content Understanding, and Cosmos DB.
Project of llm evaluation to Japanese tasks
Performs benchmarking on two Korean datasets with minimal time and effort.
An intelligent document processing solution using Azure Content Understanding and OpenAI to extract data from documents and enable natural language querying with citations.
A repository showcasing Python design patterns specifically adapted for building robust and efficient AI workflows.