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Equation 2 · Part 7 · Building a Multimodal AI Application That Actually Uses Its Inputs

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h=W0x+ΔWxh = W_0 x + \Delta W x
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What this part means

Capital delta attached to a quantity marks a difference between two values of that quantity; the article’s sign convention determines the order.

Its job in the formula

Capital delta attached to a quantity marks a difference between two values of that quantity; the article’s sign convention determines the order.

The passage around this formula

with the forward pass computing h = W0W_0 x + Δ\Delta W x against the frozen base weight W0W_0 . The method’s authors report reducing the number of trainable parameters by roughly ten thousand times and GPU memory requirements by roughly three times relative to full fine-tuning of a 175-billion-parameter model, while matching or exceeding full fine-tuning quality and adding no additional inference latency, since the low-rank update can be merged back into the base weight at deployment time [ 1 ] . QLoRA extends the same idea to quantized base weights, and its authors report finetuning a 65-billion-parameter model on a single 48-gigabyte GPU while preserving full 16-bit finetuning performance,…

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Learn the underlying idea

Addition combines quantities; subtraction measures the signed difference between them. Parentheses show what is combined before the rest of the expression is evaluated.

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Sources cited in the surrounding passage

These citations provide research context; check each source for the exact claim it supports.