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Starred repositories
Inference repo for Falcon-Perception and Falcon-OCR model, early-fusion, natively multimodal, dense Autoregressive Transformer models.
All information and news with respect to Falcon-H1 series
AMoE: Agglomerative Mixture-of-Experts Vision Foundation Models
A fast type checker and language server for Python
A Neovim plugin for displaying inline diagnostic messages with customizable styles and icons.
What happens if you try to combine dap-view and hydra.nvim? debugmaster.nvim – a modern dap-ui alternative!
Neovim Lua plugin that overrides vim.lsp.inlay_hint just to fill my desire to edit inlay hints.
Accelerating MoE with IO and Tile-aware Optimizations
📡 sshfs.nvim integrates with Neovim, using SSH and SSHFS to manage remote systems as if they were your local files.
📡 sshfs.yazi integrates seamlessly with the Yazi terminal file manager, using SSHFS to mount and unmount remote systems so you can browse, preview, and edit single files or entire directories as if…
FlexAttention based, minimal vllm-style inference engine for fast Gemma 2 inference.
A Neovim plugin that provides VSCode-style diff rendering with two-tier highlighting (line + character level) in side-by-side and inline layouts, using VSCode's algorithm implemented in C.
vim match-up: even better % 👊 navigate and highlight matching words 👊 modern matchit and matchparen. Supports both vim and neovim + tree-sitter.
A Neovim plugin that adds smooth, customizable animations to text operations like yank, paste, search, undo/redo, and more.
[ICLR '26 Oral] Official repository of the paper "AnyUp: Universal Feature Upsampling".
Performant, batteries-included completion plugin for Neovim
TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.
An extremely fast Python type checker and language server, written in Rust.
Reference PyTorch implementation and models for DINOv3
A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.