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Systems of Ashish
Particle Physics System
This project is inspired js-ts particle tried to implement on of their most popular effect from scratch no libraries
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Gemma-style Per-Layer Embeddings trained from scratch. Every transformer layer gets its own tiny token table, streamed per-token from a memory-mapped file. Beats dense at matched inference VRAM — 149.88 PPL vs 160.39 PPL.
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A Rust-based LLM inference engine focused on efficient model execution, token generation, and low-level systems performance.
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Namaste Screen
🚀 Introducing NamasteScreen: The Launcher That Fights Phone Addiction! 🇮🇳 🔥 Inspired by my conversation with Hon'ble Prime Minister of India Narendra Modi about Digital Well-Being