- Cary, NC
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06:01
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Highlights
Machine Learning
Open deep learning compiler stack for cpu, gpu and specialized accelerators
High-performance In-browser LLM Inference Engine
SkyPilot: Run AI and batch jobs on any infra (Kubernetes or 14+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, Du…
A unified framework for 3D content generation.
Refine high-quality datasets and visual AI models
Anatomic Reconstruction for Generalizable UltraSound (ARGUS) AI: A library for point-of-care ultrasound AI using MONAI and ITK
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
SAM-Med3D: An Efficient General-purpose Promptable Segmentation Model for 3D Volumetric Medical Image
Official PyTorch implementation of "AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network" in CVPR 2022.
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM (CVPR 2024)
Examples for using ONNX Runtime for machine learning inferencing.
aider is AI pair programming in your terminal
Minimal web UI for GeminiPro.
A free and open-source inpainting & image-upscaling tool powered by webgpu and wasm on the browser。| 基于 Webgpu 技术和 wasm 技术的免费开源 inpainting & image-upscaling 工具, 纯浏览器端实现。
[CVPR 2024] Paint3D: Paint Anything 3D with Lighting-Less Texture Diffusion Models, a no lighting baked texture generative model
diffusers implementation for node.js and browser
Jan is an open source alternative to ChatGPT that runs 100% offline on your computer
Segment Anything in Medical Images
🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.