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Source channel @githubtrending · Post #14845 · Jun 20

#jupyter_notebook#ai#artificial_intelligence#chatgpt#deep_learning#from_scratch#gpt#language_model#large_language_models#llm#machine_learning#python#pytorch#transformer You can learn how to build your own large language model (LLM) like GPT from scratch with clear, step-by-step guidance, including coding, training, and fine-tuning, all explained with examples and diagrams. This approach mirrors how big models like ChatGPT are made but is designed to run on a regular laptop without special hardware. You also get access to code for loading pretrained models and fine-tuning them for tasks like text classification or instruction following. This helps you deeply understand how LLMs work inside and lets you create your own functional AI assistant, gaining practical skills in AI development[1][2][3][4]. https://github.com/rasbt/LLMs-from-scratch

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@githubtrending · Post #14996 · 07/25/2025, 12:00 PM

#ocaml#c#go#java#javascript#python#r2c#ruby#sast#semgrep#static_analysis#static_code_analysis#typescript Semgrep is a fast, open-source tool that scans your code to find bugs and security issues in over 30 programming languages. It works locally on your computer or in your build system, so your code stays private. Semgrep’s rules are easy to write and understand, helping you catch problems early in development, whether in your IDE, pre-commit checks, or CI/CD pipelines. For stronger security, the Semgrep AppSec Platform offers advanced analysis, AI-powered triage, and detailed fix guidance, reducing false alarms and helping developers fix issues quickly without slowing down. This improves code quality and security efficiently. https://github.com/semgrep/semgrep

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@githubtrending · Post #15349 · 12/20/2025, 12:30 PM

#python#ai#bug_detection#code_audit#code_quality#code_review#developer_tools#devsecops#google_gemini#llm#react#sast#security_scanner#supabase#typescript#vite#vulnerability_scanner#xai **DeepAudit** is an AI-powered code audit tool using multi-agent collaboration to deeply scan projects for vulnerabilities like SQL injection, XSS, and path traversal. Import code from GitHub/GitLab or paste snippets; agents plan, analyze with RAG knowledge, and verify issues via secure Docker sandbox PoCs, generating PDF reports with fix suggestions. Deploy easily with one Docker command, supports local Ollama models for privacy, and cuts traditional tools' high false positives. **You benefit** by automating secure audits like a pro hacker—saving time, reducing errors, ensuring real exploits are caught, and speeding safe releases without manual hassle. https://github.com/lintsinghua/DeepAudit