Lists (1)
Sort Name ascending (A-Z)
- All languages
- Astro
- Awk
- Batchfile
- C
- C#
- C++
- CSS
- Clojure
- Common Lisp
- Dart
- Dockerfile
- Elm
- Emacs Lisp
- Forth
- GDScript
- Go
- HTML
- Haskell
- Haxe
- Java
- JavaScript
- Jupyter Notebook
- Kotlin
- Lua
- Markdown
- Nim
- Nix
- Objective-C
- PHP
- Perl
- PowerShell
- Python
- Q#
- QML
- Raku
- Ruby
- Rust
- SCSS
- Shell
- Svelte
- Swift
- TeX
- TypeScript
- Verilog
- Vim Script
- Vue
- WebAssembly
- sed
Starred repositories
Examples and guides for using the OpenAI API
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
The fastai book, published as Jupyter Notebooks
A guidance language for controlling large language models.
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama mode…
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
StableLM: Stability AI Language Models
Examples and guides for using the Gemini API
Draw pretty maps from OpenStreetMap data! Built with osmnx +matplotlib + shapely
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Create delightful software with Jupyter Notebooks
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
[SIGGRAPH Asia 2023] Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
The hub for EleutherAI's work on interpretability and learning dynamics
A collection of guides and examples for the Gemma open models from Google.
Representation Engineering: A Top-Down Approach to AI Transparency
Achieve the llama3 inference step-by-step, grasp the core concepts, master the process derivation, implement the code.
Official implementation of Würstchen: Efficient Pretraining of Text-to-Image Models