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Get up and running with Llama 3.1, Mistral, Gemma 2, and other large language models.
An implementation of Shazam's song matching algorithm.
A minimal Tensor Processing Unit (TPU) inspired by Google's TPUv1.
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
DataChain ๐ AI-dataframe to enrich, transform and analyze data from cloud storages for ML training and LLM apps
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
Run your own AI cluster at home with everyday devices ๐ฑ๐ป ๐ฅ๏ธโ
A framework for serving and evaluating LLM routers - save LLM costs without compromising quality!
Create LLM agents with long-term memory and custom tools ๐๐ฆ
Kickstart your MLOps initiative with a flexible, robust, and productive Python package.
Process manager and website for hosting multiple Streamlit apps
Stateful load balancer custom-tailored for llama.cpp
Production-Grade Container Scheduling and Management
Python framework for building efficient data pipelines. It promotes modularity and collaboration, enabling the creation of complex pipelines from simple, reusable components.
Material for cuda-mode lectures
Jan is an open source alternative to ChatGPT that runs 100% offline on your computer. Multiple engine support (llama.cpp, TensorRT-LLM)
A Portfolio website built with React and ThreeJS
This is a repo with links to everything you'd ever want to learn about data engineering
Get up and running with a new Python project, already set up with industry-standard tools for a fantastic development experience.
PyTorch native quantization and sparsity for training and inference
๐งฉ๐ Solve technical interview problems from Project Euler, Reddit's r/dailyprogrammer, and CodingBat in Visual Studio Code. Built on Fastify.
Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI
Notes on "Programming Massively Parallel Processors" by Hwu, Kirk, and Hajj (4th ed.)