Popular GitHub Repositories for X Vlm

?「AI 低代码平台」前后端分离 SpringBoot 2.x/3.x，SpringCloud，Ant Design&Vue3，Mybatis，Shiro！强大的代码生成器让前后端代码一键生成，无需写任何代码! 引领AI低代码开发模式 AI生成->OnlineCoding->代码生成->手工MERGE，帮助Java项目解决80%重复工作，让开发更关注业务，提高开发效率、节省成本，同时又不失灵活性

SGLang is a fast serving framework for large language models and vision language models.

Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, RTX Video Super Resolution VSR, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.

Convert AI papers to GUI，Make it easy and convenient for everyone to use artificial intelligence technology。让每个人都简单方便的使用前沿人工智能技术

Easily fine-tune, evaluate and deploy Qwen3, DeepSeek-R1, Llama 4 or any open source LLM / VLM!

This repository offers a comprehensive collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like YOLO11, RT-DETR, SAM 2, Florence-2, PaliGemma 2, and Qwen2.5VL.

An open source implementation of Microsoft's VALL-E X zero-shot TTS model. Demo is available in https://plachtaa.github.io/vallex/

2^x Image Super-Resolution

TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。

Effortless data labeling with AI support from Segment Anything and other awesome models.

OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

Nexa SDK is a comprehensive toolkit for supporting GGML and ONNX models. It supports text generation, image generation, vision-language models (VLM), Audio Language Model, auto-speech-recognition (ASR), and text-to-speech (TTS) capabilities.

Tengine is a lite, high performance, modular inference engine for embedded device

?A curated list of Awesome LLM/VLM Inference Papers with codes: WINT8/4, Flash-Attention, Paged-Attention, Parallelism, etc. ??

? 「大模型」1小时从0训练26M参数的视觉多模态VLM！? Train a 26M-parameter VLM from scratch in just 1 hours!

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

General technology for enabling AI capabilities w/ LLMs and MLLMs

StarVector is a foundation model for SVG generation that transforms vectorization into a code generation task. Using a vision-language modeling architecture, StarVector processes both visual and textual inputs to produce high-quality SVG code with remarkable precision.

oneAPI Deep Neural Network Library (oneDNN)

中文古诗自动作诗机器人，x炸天，基于tensorflow1.10 api，正在积极维护升级中，快star，保持更新！