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GitHub repos

GitHub repos

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Welcome to GitHub repos. Here you'll find valuable information on the latest trending projects. Subscribe to stay informed and gain insights from the thriving GitHub community.

Ko'proq ko'rsatish

📈 Telegram kanali GitHub repos analitikasi

GitHub repos (@github_repos) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 28 113 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 4 720-o'rinni va Hindiston mintaqasida 14 026-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 28 113 obunachiga ega bo‘ldi.

08 Noyabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 543 ga, so‘nggi 24 soatda esa 22 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 5.39% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.64% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 1 516 marta ko‘riladi; birinchi sutkada odatda 743 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 2 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent fork, typescript, claude, arbitrage, cli kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Welcome to GitHub repos. Here you'll find valuable information on the latest trending projects. Subscribe to stay informed and gain insights from the thriving GitHub community.”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 09 Noyabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

28 113
Obunachilar
+2224 soatlar
+1707 kun
+54330 kun
Postlar arxiv
dogdie233/LiarsBarEnhance A bepinex mod to enhance game experience (maybe) Language: C# #bepinex #mod Stars: 262 Issues: 2 Forks: 20 https://github.com/dogdie233/LiarsBarEnhance

konstin/sudoku-in-python-packaging Sudoku solving in python packaging Language: Python Stars: 315 Issues: 0 Forks: 0 https://github.com/konstin/sudoku-in-python-packaging

corbt/agent.exe Language: TypeScript Stars: 941 Issues: 11 Forks: 67 https://github.com/corbt/agent.exe

rhymes-ai/Allegro Allegro is a powerful text-to-video model that generates high-quality videos up to 6 seconds at 15 FPS and 720p resolution from simple text input. Language: Python Stars: 239 Issues: 10 Forks: 11 https://github.com/rhymes-ai/Allegro

adarshb3/Virtual-Try-On-Application-using-Flask-Twilio-and-Gradio This repository contains the code for a virtual try-on application built using Flask, Twilio's WhatsApp API, and Gradio's virtual try-on model. Users can send images via WhatsApp to try on garments virtually, and the results are sent back to them. Language: Python Stars: 265 Issues: 0 Forks: 29 https://github.com/adarshb3/Virtual-Try-On-Application-using-Flask-Twilio-and-Gradio

cvg/depthsplat DepthSplat: Connecting Gaussian Splatting and Depth Language: Python #feed_forward_gaussian_splatting #monocular_depth #multi_view_stereo #view_synthesis Stars: 318 Issues: 8 Forks: 9 https://github.com/cvg/depthsplat

nh2/internal-contstrained-pki Safely shareable TLS root CA for .internal networks using Name Constraints Language: Shell #openssl #pki #tls #x509 Stars: 467 Issues: 0 Forks: 10 https://github.com/nh2/internal-contstrained-pki

aotakeda/learn-thing Create mind maps to learn new things using AI. Language: TypeScript Stars: 316 Issues: 2 Forks: 13 https://github.com/aotakeda/learn-thing

awslabs/git-remote-s3 Language: Python Stars: 335 Issues: 5 Forks: 5 https://github.com/awslabs/git-remote-s3

protectai/vulnhuntr Zero shot vulnerability discovery using LLMs Language: Python #ai #llm #security #static_analysis #vulnerability_detection Stars: 381 Issues: 3 Forks: 41 https://github.com/protectai/vulnhuntr

ethanniser/NextMaster A highly performant replica of McMaster-Carr using Next.js Language: TypeScript Stars: 489 Issues: 4 Forks: 60 https://github.com/ethanniser/NextMaster

Geekgineer/YOLOs-CPP A high-performance C++ headers for real-time object detection using YOLO models, leveraging ONNX Runtime and OpenCV for seamless integration. Supports multiple YOLO versions (v5, v7, v8, v10, v11) with optimized inference on CPU and GPU. Includes sample code, scripts for image, video, and live camera inference, and tools for quantization. Language: C++ Stars: 145 Issues: 1 Forks: 16 https://github.com/Geekgineer/YOLOs-CPP

goncy/next-mercadopago Repositorio de ejemplo sobre como agregar pagos con Mercado Pago a una aplicación Next.js con App Router Language: TypeScript Stars: 188 Issues: 0 Forks: 16 https://github.com/goncy/next-mercadopago

varwara/CVE-2024-35250 PoC for the Untrusted Pointer Dereference in the ks.sys driver Language: C++ Stars: 160 Issues: 1 Forks: 39 https://github.com/varwara/CVE-2024-35250

hugohadfield/kalmangrad Automated, smooth, N'th order derivatives of non-uniformly sampled time series data Language: Python #data_science #derivatives #kalman_filter #signal_processing #smoothing Stars: 168 Issues: 1 Forks: 3 https://github.com/hugohadfield/kalmangrad

cpu0x00/Ghost Evasive shellcode loader Language: C++ Stars: 173 Issues: 3 Forks: 30 https://github.com/cpu0x00/Ghost

NiazMorshed2007/shadcn-tiptap Sets of custom extensions for tiptap editor. Language: TypeScript #editor #prosemirror #rich_text_editor #tiptap Stars: 180 Issues: 0 Forks: 2 https://github.com/NiazMorshed2007/shadcn-tiptap

lucasnewman/f5-tts-mlx Implementation of F5-TTS in MLX Language: Python #diffusion_transformer #flow_matching #mlx #text_to_speech #tts Stars: 193 Issues: 2 Forks: 17 https://github.com/lucasnewman/f5-tts-mlx

mit-han-lab/duo-attention DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads Language: Python Stars: 198 Issues: 0 Forks: 6 https://github.com/mit-han-lab/duo-attention