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Loading identity profile... Name : MUNEEB Mode : Applied AI Developer Status : building from dataset -> model -> evaluation -> product |
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PS C:\Users\MUNEEB> whoami Applied AI Developer PS C:\Users\MUNEEB> Get-Location Islamabad, Pakistan PS C:\Users\MUNEEB> Get-Mission Build AI systems from dataset -> model -> evaluation -> product. |
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PS C:\Users\MUNEEB> Get-Profile | Select-Object Focus, Output Focus Output ----- ------ Dataset engineering clean training and evaluation data Fine-tuning LoRA / QLoRA adapters with gates Retrieval RAG, embeddings, pgvector Local inference Qwen, Ollama, llama.cpp, GGUF Product engineering APIs, dashboards, auth, automation Systems fundamentals C++, OpenGL, Java, algorithms |
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PS C:\Users\MUNEEB> Get-Repositories | >> Where-Object Name -ne "muneeb-anjum0" | >> Sort-Object PushedAt -Descending | >> Select-Object -First 3 |
| PS C:\Users\MUNEEB> Open‑the‑interview |
Recently updated project repository.
Language: C++ Commits: 3 PRs: 0 Last pushed: 2026-07-20
| PS C:\Users\MUNEEB> Open‑ClassWire |
Inbox2table extracts class schedule emails from Gmail, parses timetable information, and displays organized schedules with semester filtering and multi-user persistence. Built with Flask, React, and Supabase.
Language: Python Commits: 126 PRs: 27 Last pushed: 2026-07-20
| PS C:\Users\MUNEEB> Open‑NOPE |
Local-first AppSec review workbench for authorized repository and URL scans, with deterministic scanners, evidence-gated findings, reports, drift, and optional local Qwen explanations.
Language: Python Commits: 99 PRs: 0 Last pushed: 2026-07-19
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PS C:\Users\MUNEEB> Get-Stack -Grouped AI/Data PyTorch, Hugging Face, Qwen, LoRA, QLoRA, RAG, pgvector Inference Ollama, llama.cpp, GGUF, local-first model routing Web/API React, Next.js, TypeScript, FastAPI, Flask, Go, Gin Storage PostgreSQL, MongoDB, Firestore, Redis, SQLite Quality Playwright, pytest, Vitest, evaluation gates, CI checks Native C++, OpenGL, Dear ImGui, Java |
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PS C:\Users\MUNEEB> Get-Rules [1] Build the dataset before trusting the model. [2] Measure failure cases, not vibes. [3] Keep inference replaceable. [4] Protect credentials and user data by default. [5] Ship the smallest useful system. |
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PS C:\Users\MUNEEB> exit build the data; test the model; ship the system |

