Stars
awesome grounding: A curated list of research papers in visual grounding
A natural language interface for computers
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
FFCV: Fast Forward Computer Vision (and other ML workloads!)
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 project demonstrating Lidar related AI solutions, including three GPU accelerated Lidar/camera DL networks (PointPillars, CenterPoint, BEVFusion) and the related libs (cuPCL, 3D SparseConvolution…
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
An open-source tool-augmented conversational language model from Fudan University
Segment-anything related awesome extensions/projects/repos.
PyTorch code and models for the DINOv2 self-supervised learning method.
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform
A CLI that converts natural language to shell commands.
Automated dense category annotation engine that serves as the initial semantic labeling for the Segment Anything dataset (SA-1B).
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.
Baby-DALL3: Annotation anything in visual tasks and Generate anything just all in one-pipeline with GPT-4 (a small baby of DALL·E 3).
Making large AI models cheaper, faster and more accessible
[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Lightweight Hyperparameter Optimization 🚂
Cockpit: A Practical Debugging Tool for Training Deep Neural Networks