Github Top Repositories
Top GitHub repositories in one place π Explore the best projects in programming, AI, data science, and more.
Ko'proq ko'rsatishπ Telegram kanali Github Top Repositories analitikasi
Github Top Repositories (@githubre) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 14 150 obunachidan iborat bo'lib, TaΚΌlim toifasida 14 019-o'rinni va Hindiston mintaqasida 28 451-o'rinni egallagan.
π Auditoriya koβrsatkichlari va dinamika
Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ sanasidan buyon loyiha tez oβsib, 14 150 obunachiga ega boβldi.
28 Avgust, 2026 dagi oxirgi maβlumotlarga koβra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 273 ga, soβnggi 24 soatda esa 9 ga oβzgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya oβrtacha 1.05% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.70% ini tashkil etuvchi reaksiyalarni toβplaydi.
- Post qamrovi: Har bir post oβrtacha 149 marta koβriladi; birinchi sutkada odatda 99 ta koβrish yigβiladi.
- Reaksiyalar va oβzaro taβsir: Auditoriya faol: har bir postga oβrtacha 1 ta reaksiya keladi.
- Tematik yoβnalishlar: Kontent repository, fork, programming, statistic, description kabi asosiy mavzularga jamlangan.
π Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taβriflaydi:
βTop GitHub repositories in one place π
Explore the best projects in programming, AI, data science, and more.β
Yuqori yangilanish chastotasi (oxirgi maβlumot 29 Avgust, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boβlib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni TaΚΌlim toifasidagi muhim taβsir nuqtasiga aylantirishini koβrsatadi.
no tracking, customizable homepage, and notifications for subscribed channels. Invidious can be used by selecting a public instance from the list or by hosting it yourself.
From a technical standpoint, Invidious has embedded video support and a developer API, and it does not use official YouTube APIs. The project is available in many languages and has a strong focus on community involvement, with opportunities to contribute code and translate the platform.
The target audience for Invidious includes anyone looking for a private and ad-free YouTube experience. Whether you're a casual user or a developer, Invidious provides a unique alternative to the traditional YouTube platform.
Invidious is all about taking back control of your YouTube experience - it's your videos, your way.
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π§ Channel: https://t.me/GithubReairllm package using pip install airllm and initialize the model with AutoModel.from_pretrained("model_id"). You can also enable model compression for up to 3x inference speedup by passing the compression argument.
AirLLM supports a wide range of models, including ChatGLM, QWen, Baichuan, and more. It's perfect for researchers, developers, and enthusiasts looking to push the boundaries of language modeling.
In short, AirLLM is a powerful tool that makes large language models more accessible and efficient. With its ease of use and impressive performance, it's a must-try for anyone working with language models: run bigger models, faster, and on less hardware.
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π§ Channel: https://t.me/GithubRedrim CLI tool for a one-click deployment or set it up with Docker Compose for a quick start. The platform is open source with a permissive MIT license, and its documentation provides detailed guides for setup, configuration, and development.
Kaneo is suitable for teams looking for a simple, efficient, and customizable project management solution. Whether you're a developer, a project manager, or a team lead, Kaneo's flexible and adaptable nature makes it a great choice.
From a technical standpoint, Kaneo's API and web services can be configured and customized to meet specific needs, and its Kubernetes deployment options make it easy to scale and manage.
In short, Kaneo is a breath of fresh air in the world of project management tools - simple, fast, and efficient. Try it out and see the difference for yourself: with Kaneo, less is more, and that's what makes it great.
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π§ Channel: https://t.me/GithubReTensorFlow and PyTorch, as well as ethics in AI.
The curriculum is divided into sections, including an Introduction to AI, Symbolic AI, and Introduction to Neural Networks. Each section includes practical lessons, quizzes, and labs to help reinforce learning.
One of the key features of this repository is its multi-language support, with translations available in over 50 languages. To get started, you can clone the repository locally, and to make the process faster, you can use sparse checkout to exclude translations.
Here's an example of how to do this:
git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git
cd AI-For-Beginners
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'
The repository also includes a mindmap of the course to help visualize the topics covered. You can join the community and get involved through the Microsoft Foundry Discord server.
Overall, the Microsoft AI-For-Beginners repository is a comprehensive resource for anyone looking to learn about AI. So, dive in and start exploring - with this curriculum, you'll be well on your way to becoming an AI master in no time!
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π§ Channel: https://t.me/GithubRemake setup command to run the setup wizard, which guides you through choosing an LLM provider and configuring your setup.
You can also use the make dev command for local development or make docker-start for Docker development. For a quick start, you can clone the repository, run the setup wizard, and then start the application using make up.
DeerFlow 2.0 is a ground-up rewrite with no shared code with version 1, and it's designed to be extensible and customizable. The project has a official website with real demos and a sister project called LLM Space.
The recommended models include GPT-4o, Gemini 2.5 Flash, and Qwen3 32B. You can also use the embedded Python client to interact with DeerFlow.
One-line takeaway: With DeerFlow, you can build a super agent harness that can do almost anything, and it's free and open-source.
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π§ Channel: https://t.me/GithubRenpx. You can install all skills at once or choose specific ones to install.
Some of the skills available in k-skill include:
- SRT and KTX booking
- Lottery checks
- Interactions with government services like tax and business registration
- Automated tasks for Korean services like banking and insurance
The technical highlights of k-skill include its support for multiple coding agents and its use of Node.js for installation and execution.
This project is aimed at developers who want to automate tasks related to Korean services. If you're interested in contributing to k-skill, be sure to check out the CONTRIBUTING.md file for more information.
In short, k-skill is an amazing resource for automating tasks related to Korean services - and with great power comes great automation!
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π§ Channel: https://t.me/GithubRememory layering with heterogeneous storage, symbolic memory using Mermaid syntax, and context offloading with `node_id` tracing. This approach enables agents to reason better, not just remember more.
Technical highlights include a unified architectural paradigm with short-term context layering, long-term personalization layering, and skill generation layering. The system also ensures full traceability and lossless recovery through a deterministic path from high-level abstractions to ground-truth evidence.
The target audience includes developers and users of OpenClaw and Hermes agents, who can integrate this plugin to enhance their agents' memory capabilities.
To get started, users can follow the quick start guide, which includes installation and configuration instructions for OpenClaw and Hermes.
In summary, the TencentDB Agent Memory plugin is a powerful tool for improving agent performance by enabling them to learn from experience and retain context. Let the agents remember, so humans can innovate.
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π§ Channel: https://t.me/GithubReO-Voxel, which allows for the reconstruction and generation of complex 3D assets with sharp features and full PBR materials. The model boasts high-quality, resolution, and efficiency, generating high-resolution fully textured assets with exceptional fidelity.
Some of the key features of TRELLIS.2 include:
- Arbitrary topology handling: The O-Voxel representation can handle complex structures without lossy conversion, including open surfaces, non-manifold geometry, and internal enclosed structures.
- Rich texture modeling: The model supports arbitrary surface attributes, including base color, roughness, metallic, and opacity, enabling photorealistic rendering and transparency support.
- Minimalist processing: Data processing is streamlined for instant conversions that are fully rendering-free and optimization-free.
To use TRELLIS.2, you'll need to install the dependencies, including the CUDA Toolkit and Conda, and then clone the repository. You can then use the pretrained model for image-to-3D generation or PBR texture generation. The repository also provides a web demo for easy testing.
From a technical standpoint, TRELLIS.2 is a 4B-parameter model that utilizes a Sparse 3D VAE with 16Γ spatial downsampling to encode assets into a compact latent space. The model is designed for high-performance and can generate high-resolution assets with exceptional fidelity.
The target audience for TRELLIS.2 includes researchers, developers, and artists working with 3D generation and image-to-3D applications. With its powerful features and streamlined processing, TRELLIS.2 is an ideal choice for anyone looking to push the boundaries of 3D generation.
In short, TRELLIS.2 is a game-changer for 3D generation, offering unparalleled fidelity, efficiency, and flexibility - and with its open-source availability, the possibilities are endless!
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π§ Channel: https://t.me/GithubRepip or a package manager, and power users can run the devel branch for the latest features. The community is active, with a forum for asking questions, getting help, and interacting with other users.
From a technical perspective, Ansible focuses on security and auditability, and allows module development in any dynamic language. The project is coded in a variety of languages, including Python, and has a devel branch for ongoing development.
Ansible is suitable for a wide range of users, from system administrators to developers, and is widely used in the industry.
The project is licensed under the GNU General Public License v3.0 or later.
In short, Ansible is all about making complex IT tasks radically simple - and that's a game-changer!
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π§ Channel: https://t.me/GithubReno tracking, customizable homepage, and audio-only mode. Users can import subscriptions from YouTube and other platforms, and export them as needed.
From a technical standpoint, Invidious has an embedded video support and a developer API, making it a great option for developers. The project is hosted on GitHub and has a large community of contributors, with translations available in many languages.
To get started, users can select a public instance or host Invidious themselves by following the installation instructions. The project is suitable for anyone looking for a private and customizable YouTube experience.
Invidious is perfect for those who want to ditch YouTube's ads and tracking - and it's completely free and open-source. Join the Invidious community today and experience the power of open-source video sharing!
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π§ Channel: https://t.me/GithubRePython 3.12, Torch 2.8.0+cu128, and Gradio 6.20. It also utilizes several AI models, including Whisper, F5-TTS, and CosyVoice, to deliver high-quality speech recognition and voice cloning capabilities.
Voice-Pro is designed for a range of users, including creators, researchers, and multilingual professionals. It offers a robust alternative to ElevenLabs, with advanced voice solutions and a user-friendly interface.
In short, Voice-Pro is a powerful tool for anyone looking to leverage the power of AI for speech recognition, translation, and multilingual dubbing - and with its open-source code and free distribution, the possibilities are endless!
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π§ Channel: https://t.me/GithubRe