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Update quantization.md

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docs/source/conceptual/quantization.md
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@ -8,7 +8,7 @@ GPTQ is a post-training quantization method to make the model smaller. It quanti
Given a layer \(l\) with weight matrix \(W_{l}\) and layer input \(X_{l}\), find quantized weight \(\hat{W}_{l}\):
$${\hat{W}{l}}^{*} = argmin{\hat{W_{l}}} |W_{l}X-\hat{W}{l}X|^{2}{2}) \}$$
$$({\hat{W}_{l}}^{*} = argmin_{\hat{W_{l}}} ||W_{l}X-\hat{W}_{l}X||^{2}_{2})$$
TGI allows you to both run an already GPTQ quantized model (see available models [here](https://huggingface.co/models?search=gptq)) or quantize a model of your choice using quantization script by simply passing --quantize like below 👇