Meta AI Engineering v2: make download.sh executable (#695)

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Derived & scientifically synthesized from Meta AI Engineering.
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Executive Summary

An AI breakthrough and engineering milestone from Meta AI Engineering shifts the frontier of weights openness, local inference throughput (GGUF, TensorRT, vLLM), or reasoning compute benchmarks.

Artificial Intelligence Architecture & Model Evaluation

From an artificial intelligence architecture, model weights governance, and inference efficiency perspective: - **Weights Accessibility & Sovereignty:** Evaluates whether weights are open for private self-hosting or locked behind centralized cloud APIs. - **Quantization & Edge Performance:** Kernel optimizations (4-bit/8-bit GGUF, AWQ, EXL2) allow high tokens-per-second on consumer GPUs and Apple Silicon. - **Reasoning & Architectural Scaling:** Scrutinizes mixture-of-experts (MoE), attention mechanisms, and fine-tuning datasets against open community benchmarks.

Impact on the Open Ecosystem

Protects developers and enterprises from proprietary black-box entrapment, fostering auditable, sovereign AI infrastructure.

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