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๐Ÿš€ Meet rasbt/LLMs-from-scratch: a gem from today's GitHub trending list.

๐Ÿ”— https://github.com/rasbt/LLMs-from-scratch
๐Ÿ“ Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€

The rasbt/LLMs-from-scratch GitHub repository provides a comprehensive guide to building a large language model (LLM) from scratch. The repository is the official code companion to the book Build a Large Language Model (From Scratch). It covers the development, pretraining, and finetuning of a GPT-like LLM, with a focus on hands-on implementation using PyTorch.

The repository includes code notebooks for each chapter, covering topics such as text data processing, attention mechanisms, and model finetuning. It also provides a troubleshooting guide and a setup guide for installing Python and required packages.

The target audience is developers and researchers interested in LLMs, with a strong foundation in Python programming. The repository is designed to be accessible, with code that can run on conventional laptops.

In summary, the rasbt/LLMs-from-scratch repository offers a unique opportunity to learn about LLMs by building one from scratch - and that's a powerful way to learn.

โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
๐Ÿง  Channel: https://t.iss.one/GithubRe
โค1
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๐ŸŒŸ datawhalechina/hello-agents caught my eye on GitHub Trending today.

๐Ÿ”— https://github.com/datawhalechina/hello-agents
๐Ÿ“ ๐Ÿ“š ใ€ŠไปŽ้›ถๅผ€ๅง‹ๆž„ๅปบๆ™บ่ƒฝไฝ“ใ€‹โ€”โ€”ไปŽ้›ถๅผ€ๅง‹็š„ๆ™บ่ƒฝไฝ“ๅŽŸ็†ไธŽๅฎž่ทตๆ•™็จ‹
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€

Hello-Agents ๆ˜ฏไธ€ไธชๅผ€ๆบ้กน็›ฎ๏ผŒๆ—จๅœจไปŽๅŸบ็ก€็†่ฎบๅˆฐๅฎž้™…ๅบ”็”จ๏ผŒๅ…จ้ขๆŽŒๆกๆ™บ่ƒฝไฝ“็ณป็ปŸ็š„่ฎพ่ฎกไธŽๅฎž็Žฐใ€‚่ฏฅ้กน็›ฎๅŒ…ๅซไบ”ๅคง้ƒจๅˆ†๏ผŒๅŒ…ๆ‹ฌๆ™บ่ƒฝไฝ“ไธŽ่ฏญ่จ€ๆจกๅž‹ๅŸบ็ก€ใ€ๆž„ๅปบๅคง่ฏญ่จ€ๆจกๅž‹ๆ™บ่ƒฝไฝ“ใ€้ซ˜็บง็Ÿฅ่ฏ†ๆ‰ฉๅฑ•ใ€็ปผๅˆๆกˆไพ‹่ฟ›้˜ถๅ’Œๆฏ•ไธš่ฎพ่ฎกๅŠๆœชๆฅๅฑ•ๆœ›ใ€‚้€š่ฟ‡่ฟ™ไธช้กน็›ฎ๏ผŒ่ฏป่€…ๅฏไปฅ็ณป็ปŸๆ€งๅœฐๅญฆไน ๆ™บ่ƒฝไฝ“็š„ๆฆ‚ๅฟตใ€ๅކๅฒใ€็ปๅ…ธ่Œƒๅผใ€ๅบ”็”จๅ’Œๆž„ๅปบ๏ผŒไปŽ่€Œๆˆไธบไธ€ๅๆ™บ่ƒฝไฝ“็ณป็ปŸ็š„ๆž„ๅปบ่€…ใ€‚

ไธป่ฆ็‰น็‚น๏ผš
- ๅผ€ๆบๅ…่ดน
- ็†่ฎบไธŽๅฎž่ทตๅนถ้‡
- ้€‚ๅˆ AI ๅผ€ๅ‘่€…ใ€่ฝฏไปถๅทฅ็จ‹ๅธˆใ€ๅœจๆ กๅญฆ็”Ÿๅ’Œ่‡ชๅญฆ่€…
- ๅŒ…ๅซ้…ๅฅ—ไปฃ็ ๅ’Œ่ง†้ข‘่ฏพ็จ‹

่ดก็Œฎ๏ผš
- ๆŠฅๅ‘Š Bug
- ๆๅ‡บๅปบ่ฎฎ
- ๅฎŒๅ–„ๅ†…ๅฎน
- ๅˆ†ไบซๅฎž่ทต

่‡ด่ฐข๏ผš
- ๆ ธๅฟƒ่ดก็Œฎ่€…
- Extra-Chapter ่ดก็Œฎ่€…
- ็‰นๅˆซๆ„Ÿ่ฐข

ๅฆ‚ๆžœ่ฟ™ไธช้กน็›ฎๅฏนไฝ ๆœ‰ๅธฎๅŠฉ๏ผŒ่ฏท็ป™ๆˆ‘ไปฌไธ€ไธช Star๏ผ
print("Hello-Agents: Your journey to mastering intelligent agents starts here!")

ๆ€ป็ป“: Hello-Agents ๆ˜ฏไธ€ไธชๅธฎๅŠฉไฝ ไปŽ้›ถๅผ€ๅง‹ๆž„ๅปบๆ™บ่ƒฝไฝ“็ณป็ปŸ็š„้กน็›ฎ๏ผŒๅŠ ๅ…ฅๆˆ‘ไปฌ๏ผŒไธ€่ตทๆŽข็ดขๆ™บ่ƒฝไฝ“็š„ๅฅ‡ๅฆ™ไธ–็•Œ๏ผ

โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
๐Ÿง  Channel: https://t.iss.one/GithubRe
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โšก yikart/AiToEarn is making waves. Here's the full picture.

๐Ÿ”— https://github.com/yikart/AiToEarn
๐Ÿ“ Let's use AI to Earn!
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€

AiToEarn is an AI-powered content marketing platform designed for solo entrepreneurs, creators, and businesses to build, distribute, and monetize content on multiple global platforms. The platform supports 12 major channels, including TikTok, YouTube, Facebook, and Instagram.

Key features include:
- Monetize: helps creators earn money through content sales and promotions
- Publish: one-click content distribution across multiple platforms
- Engage: automates content interaction and operations
- Create: AI-powered content creation for videos, images, and more

Usage is straightforward, with five methods to get started:
1. Directly using the website
2. Through OpenClaw
3. With Claude or other AI assistants
4. Docker one-click deployment
5. Source code development

Technical highlights include support for Node.js 20.18.x and a MIT license. The platform is suitable for creators, entrepreneurs, and businesses looking to streamline their content marketing efforts.

In a nutshell, AiToEarn is your one-stop-shop for content creation, distribution, and monetization โ€“ making content marketing easier and more efficient than ever.

โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
๐Ÿง  Channel: https://t.iss.one/GithubRe
๐ŸŽฏ HKUDS/AI-Trader landed on trending. Worth a proper look.

๐Ÿ”— https://github.com/HKUDS/AI-Trader
๐Ÿ“ "AI-Trader: 100% Fully-Automated Agent-Native Trading"
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€

Introduction to AI-Trader: The AI-Trader platform is designed to be an agent-native trading platform, allowing AI agents to exchange ideas and sharpen their trading skills. This platform supports all major AI agents and enables them to join in seconds by sending a simple message.

Key Features: The platform offers instant agent integration, collective intelligence trading, cross-platform signal sync, one-click copy trading, universal market access, and a reward system for publishing signals and gaining followers.

Usage: There are two ways to join the platform - for agent traders and human traders. Agent traders can connect instantly by sending a message, while human traders can join directly in three simple steps.

Technical Highlights: The platform uses a modular architecture, with a FastAPI web service and a React frontend. It also has a comprehensive documentation set, including an agent integration guide, user guide, and API specifications.

Audience: The platform is designed for both AI agents and human traders, providing a unique opportunity for collaboration and knowledge sharing.

Punchy One-Liner: With AI-Trader, unleash the power of collective intelligence in trading and take your investments to the next level!

โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
๐Ÿง  Channel: https://t.iss.one/GithubRe
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๐Ÿ” Deep-diving into tinyhumansai/openhuman โ€” fresh off the trending list.

๐Ÿ”— https://github.com/tinyhumansai/openhuman
๐Ÿ“ Your Personal AI super intelligence. Private, Simple and extremely powerful.
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€

OpenHuman is an open-source, AI-powered assistant that simplifies daily life by integrating with various tools and services. It's designed to be simple, UI-first, and human-centric, allowing users to get started quickly without requiring terminal access.

Key features include:
- 118+ third-party integrations with one-click OAuth
- Auto-fetch for pulling fresh data into the Memory Tree
- A local-first knowledge base built from user data and activity
- Batteries included: web search, web-fetch scraper, coder toolset, and native voice

Usage involves downloading and installing OpenHuman, then connecting accounts to enable auto-fetch and Memory Tree. The project is open-source and free, with a GNU license.

Technical highlights include:
- TokenJuice for smart token compression, reducing cost and latency
- Model routing for sending tasks to the right LLM
- Local AI via Ollama for on-device workloads

The target audience is anyone looking for a private, simple, and powerful AI assistant.

Start your OpenHuman journey today and experience the future of AI-powered assistance!

โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
๐Ÿง  Channel: https://t.iss.one/GithubRe
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โšก rohitg00/agentmemory is making waves. Here's the full picture.

๐Ÿ”— https://github.com/rohitg00/agentmemory
๐Ÿ“ #1 Persistent memory for AI coding agents based on real-world benchmarks
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€

Agentmemory is a persistent memory solution for AI coding agents, allowing them to recall previous conversations and maintain context. The key features include auto-capture of agent interactions, searchable memory, and injecting context into new sessions.

To use agentmemory, simply run npx @agentmemory/agentmemory and it will start capturing your agent's interactions. It supports a wide range of agents, including Claude Code, Cursor, Gemini CLI, and many more, through MCP, REST API, or hooks.

The technical highlights of agentmemory include its high retrieval accuracy of 95.2% R@5, significant token savings, and seamless integration with various agents.

Agentmemory is designed for developers and users of AI coding agents who want to improve their productivity and efficiency by reducing the need for re-explaining and re-discovering information.

In a nutshell, agentmemory revolutionizes the way AI coding agents interact with users, and its impact can be summarized as: Your agent will never forget what you told it again.

โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
๐Ÿง  Channel: https://t.iss.one/GithubRe