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📝 Description: The GEP-Powered Self-Evolution Engine for AI Agents. Genome Evolution Protocol. | evomap.ai

🔗 Repository URL: https://github.com/EvoMap/evolver

🌐 Website: https://evomap.ai

📖 Readme: https://github.com/EvoMap/evolver#readme

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📝 Description: Claude Code skill to support Android app's reverse engineering

🔗 Repository URL: https://github.com/SimoneAvogadro/android-reverse-engineering-skill

📖 Readme: https://github.com/SimoneAvogadro/android-reverse-engineering-skill#readme

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📝 Description: No description available

🔗 Repository URL: https://github.com/lukilabs/craft-agents-oss

📖 Readme: https://github.com/lukilabs/craft-agents-oss#readme

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📝 Description: Build your own AI SRE agents. The open source toolkit for the AI era ✨

🔗 Repository URL: https://github.com/Tracer-Cloud/opensre

🌐 Website: https://opensre.com

📖 Readme: https://github.com/Tracer-Cloud/opensre#readme

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💻 Programming Languages: Python

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🔥 Trending Repository: t3code

📝 Description: No description available

🔗 Repository URL: https://github.com/pingdotgg/t3code

🌐 Website: https://t3.codes

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📝 Description: Easy-to-understand AI learning resources for beginners.

🔗 Repository URL: https://github.com/ConardLi/easy-learn-ai

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📝 Description: AI You Control: Choose your models. Own your data. Eliminate vendor lock-in.

🔗 Repository URL: https://github.com/thunderbird/thunderbolt

🌐 Website: https://thunderbolt.io

📖 Readme: https://github.com/thunderbird/thunderbolt#readme

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🔥 Trending Repository: DeepGEMM

📝 Description: DeepGEMM: clean and efficient FP8 GEMM kernels with fine-grained scaling

🔗 Repository URL: https://github.com/deepseek-ai/DeepGEMM

📖 Readme: https://github.com/deepseek-ai/DeepGEMM#readme

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📝 Description: Claude Desktop for Debian-based Linux distributions

🔗 Repository URL: https://github.com/aaddrick/claude-desktop-debian

📖 Readme: https://github.com/aaddrick/claude-desktop-debian#readme

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📝 Description: Enterprise Architecture Governance & Vendor Procurement Toolkit

🔗 Repository URL: https://github.com/tractorjuice/arc-kit

🌐 Website: https://arckit.org/

📖 Readme: https://github.com/tractorjuice/arc-kit#readme

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📝 Description: FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.

🔗 Repository URL: https://github.com/Fincept-Corporation/FinceptTerminal

🌐 Website: https://fincept.in

📖 Readme: https://github.com/Fincept-Corporation/FinceptTerminal#readme

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📝 Description: Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface

🔗 Repository URL: https://github.com/koala73/worldmonitor

🌐 Website: https://worldmonitor.app

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📝 Description: A black hole for Internet advertisements

🔗 Repository URL: https://github.com/pi-hole/pi-hole

🌐 Website: https://pi-hole.net

📖 Readme: https://github.com/pi-hole/pi-hole#readme

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📝 Description: Xray, Penetrates Everything. Also the best v2ray-core. Where the magic happens. An open platform for various uses.

🔗 Repository URL: https://github.com/XTLS/Xray-core

🌐 Website: https://t.iss.one/projectXray

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📝 Description: Code search MCP for Claude Code. Make entire codebase the context for any coding agent.

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📝 Description: A flexible enhancer for YouTube on iOS

🔗 Repository URL: https://github.com/dayanch96/YTLite

📖 Readme: https://github.com/dayanch96/YTLite#readme

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📝 Description: A curated collection of 1000+ agent skills from official dev teams and the community, compatible with Claude Code, Codex, Gemini CLI, Cursor, and more.

🔗 Repository URL: https://github.com/VoltAgent/awesome-agent-skills

🌐 Website: https://officialskills.sh/

📖 Readme: https://github.com/VoltAgent/awesome-agent-skills#readme

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🔥 Google Colab has added the option of retraining 500+ open-source neural networks

Unsloth has released a convenient notebook for configuring models.

Instructions:

1. Open the page in Colab: https://colab.research.google.com/github/unslothai/unsloth/blob/main/studio/Unsloth_Studio_Colab.ipynb

2. Run the blocks and the Unsloth Studio itself.

3. Select a model and a dataset.

4. Click "Start Training" and monitor the progress in real time.

5. Everything is ready - you can immediately compare the regular and fine-tuned versions of the model in the chat.