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Believer's Projects

qv2ray icon qv2ray

:star: Linux / Windows / macOS 跨平台 V2Ray 客户端 | 支持 VMess / VLESS / SSR / Trojan / Trojan-Go / NaiveProxy / HTTP / HTTPS / SOCKS5 | 使用 C++ / Qt 开发 | 可拓展插件式设计 :star:

repvgg icon repvgg

RepVGG: Making VGG-style ConvNets Great Again

text-generation-webui icon text-generation-webui

A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.

tnn icon tnn

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.

tvm icon tvm

Open deep learning compiler stack for cpu, gpu and specialized accelerators

ultralytics icon ultralytics

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

whisper icon whisper

Robust Speech Recognition via Large-Scale Weak Supervision

workflow icon workflow

C++ Parallel Computing and Asynchronous Networking Engine

x-anylabeling icon x-anylabeling

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

yoloair icon yoloair

🔥🔥🔥YOLOv5, YOLOv6, YOLOv7, PPYOLOE, YOLOX, YOLOR, YOLOv4, YOLOv3, PPYOLO, PPYOLOv2, Transformer, Attention, TOOD and Improved-YOLOv5-YOLOv7... Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀

yolov5 icon yolov5

YOLOv5 in PyTorch > ONNX > CoreML > TFLite

yolov5_magic icon yolov5_magic

🚀🚀🚀一款面向改进Yolov5的开源仓库,提供丰富的魔改Yolov5方法 An open source repository for improving Yolov5, providing rich magic methods

yolov5_quant_sample icon yolov5_quant_sample

This is 8-bit quantization sample for yolov5. Both PTQ, QAT and Partial Quantization have been implemented, and present the results based on yolov5s.

yolov7 icon yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

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