Weights are the millions or billions of adjustable numbers a model learns during training; they encode everything it knows. Parameter count is shorthand for scale — a 7-billion-parameter model is smaller, cheaper, and faster than a 70-billion one, usually at some accuracy cost.
The book · Volume 6 of 7
AI for Video: A Complete Guide to Intelligence in Video Products: From Models and Inference to Computer Vision, Speech, Search, and Generative Video
Model weights decide size, memory and cost, so parameter count is the first number to check before picking a model. This volume covers model weights in its ML minimum: parameter counts and quantization, model artifacts, open-weights licensing, and the open-versus-closed procurement decision. Written by Nikolay Sapunov, CEO at Fora Soft.
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