From 2b49732d37e28e4696aafd8e69ab4a258fea0a81 Mon Sep 17 00:00:00 2001 From: sgolebiewski-intel Date: Thu, 14 Nov 2024 15:02:16 +0100 Subject: [PATCH] Align info on NNCF and Optimum Intel --- .../weight-compression/4-bit-weight-quantization.rst | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/docs/articles_en/openvino-workflow/model-optimization-guide/weight-compression/4-bit-weight-quantization.rst b/docs/articles_en/openvino-workflow/model-optimization-guide/weight-compression/4-bit-weight-quantization.rst index 4b3b9cecdc23d8..c80f663001434f 100644 --- a/docs/articles_en/openvino-workflow/model-optimization-guide/weight-compression/4-bit-weight-quantization.rst +++ b/docs/articles_en/openvino-workflow/model-optimization-guide/weight-compression/4-bit-weight-quantization.rst @@ -143,7 +143,12 @@ environment by running the following command: pip install optimum[openvino] If the model comes from `Hugging Face `__ and is supported -by Optimum, it may be easier to use the Optimum Intel API to perform weight compression. +by Optimum, it may be easier to use the **Optimum Intel API**, which employs NNCF weight +compression capabilities to optimize various large Transformer models. + +The NNCF ``nncf.compress_weights()`` API, with most of its options, is exposed in the +``.from_pretrained()`` method of Optimum Intel classes. Optimum also has several datasets +for data-aware quantization available out-of-the-box. .. tab-set::