[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

LLM inference in C/C++

Go msort - linter that sorts methods

Addon for Storybook that generates test code for your stories.

The strictest and most opinionated python linter ever!

Algorithms, papers, datasets, performance comparisons for Document AI. Continuously updating.

Minimalist ML framework for Rust

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

Official implementation of Character Region Awareness for Text Detection (CRAFT)

Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022

Export Donut model to onnx and run it with onnxruntime

python parser for human readable dates

LLM training in simple, raw C/CUDA

Schedule-Free Optimization in PyTorch

Datasets, Transforms and Models specific to Computer Vision

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

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.

Enterprise graph machine learning framework for billion-scale graphs for ML scientists and data scientists.

🤗 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.

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.

A library for training and deploying machine learning models on Amazon SageMaker

Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.

Grok open release

The official repo for the paper "VeCLIP: Improving CLIP Training via Visual-enriched Captions"

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution