- Boston, MA
- femtomc.github.io
Highlights
- Pro
Stars
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Empowering everyone to build reliable and efficient software.
Vim-fork focused on extensibility and usability
Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.
Rich is a Python library for rich text and beautiful formatting in the terminal.
A markup-based typesetting system that is powerful and easy to learn.
A community-maintained Python framework for creating mathematical animations.
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Firefly III: a personal finances manager
An Emacs framework for the stubborn martian hacker
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Visualize Your Ideas With Code
pix2tex: Using a ViT to convert images of equations into LaTeX code.
GPU & Accelerator process monitoring for AMD, Apple, Huawei, Intel, NVIDIA and Qualcomm
A minimal GPU design in Verilog to learn how GPUs work from the ground up
Create beautiful diagrams just by typing notation in plain text.
Lean 4 programming language and theorem prover
A friendly programming language from the future
The Rocq Prover is an interactive theorem prover, or proof assistant. It provides a formal language to write mathematical definitions, executable algorithms and theorems together with an environmen…
Safe Rust bridge for creating Erlang NIF functions
Write expressive, high-performance parsers with ease.
Backlog.md - A tool for managing project collaboration between humans and AI Agents in a git ecosystem
A machine learning compiler for GPUs, CPUs, and ML accelerators