From 2585510f24145bade43fddb238a72198556ba7cf Mon Sep 17 00:00:00 2001 From: andreyanufr Date: Tue, 12 Nov 2024 11:11:50 +0100 Subject: [PATCH] Andreyan/fix links to mx docs (#3076) ### Reason for changes Irrelevant links to MX document. --------- Co-authored-by: Aleksandr Suslov --- .../post_training_compression/weights_compression/Usage.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/usage/post_training_compression/weights_compression/Usage.md b/docs/usage/post_training_compression/weights_compression/Usage.md index 31beb7dcfeb..1c5cd1257a7 100644 --- a/docs/usage/post_training_compression/weights_compression/Usage.md +++ b/docs/usage/post_training_compression/weights_compression/Usage.md @@ -22,7 +22,7 @@ The Weights Compression algorithm is aimed at compressing the weights of the mod ### Supported modes By default, weights are compressed asymmetrically to 8-bit integer data type - "INT8_ASYM" mode. -OpenVINO backend also supports 4 modes of mixed precision weight quantization with a 4-bit data type as a primary precision - INT4_SYM, INT4_ASYM, NF4, E2M1. The primary precision in case of INT4_SYM mode is signed 4-bit integer and weights are quantized to it [symmetrically](/docs/usage/training_time_compression/other_algorithms/LegacyQuantization.md#symmetric-quantization) without zero point. In case of INT4_ASYM mode - unsigned 4-bit integer and weight are quantized to it [asymmetrically](/docs/usage/training_time_compression/other_algorithms/LegacyQuantization.md#asymmetric-quantization) with a typical non-fixed zero point. In case of NF4 mode - [nf4](https://arxiv.org/pdf/2305.14314v1.pdf) data type without zero point. In case of E2M1 mode - [e2m1](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf) data type without zero point and has 8bit [E8M0](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf) scale. +OpenVINO backend also supports 4 modes of mixed precision weight quantization with a 4-bit data type as a primary precision - INT4_SYM, INT4_ASYM, NF4, E2M1. The primary precision in case of INT4_SYM mode is signed 4-bit integer and weights are quantized to it [symmetrically](/docs/usage/training_time_compression/other_algorithms/LegacyQuantization.md#symmetric-quantization) without zero point. In case of INT4_ASYM mode - unsigned 4-bit integer and weight are quantized to it [asymmetrically](/docs/usage/training_time_compression/other_algorithms/LegacyQuantization.md#asymmetric-quantization) with a typical non-fixed zero point. In case of NF4 mode - [nf4](https://arxiv.org/pdf/2305.14314v1.pdf) data type without zero point. In case of E2M1 mode - [e2m1](https://arxiv.org/pdf/2310.10537) data type without zero point and has 8bit [E8M0](https://arxiv.org/pdf/2310.10537) scale. All 4-bit modes have a grouped quantization support, when small group of weights (e.g. 128) in the channel dimension share quantization parameters (scale). All embeddings, convolutions and last linear layers are always compressed to a backup mode, which is "INT8_ASYM", by default. To quantize embeddings and last linear layers to 4-bit, use `all_layers=True`. Percent of the rest layers compressed to 4-bit can be configured by "ratio" parameter. E.g. ratio=0.9 means 90% of layers compressed to the corresponding 4-bit data type and the rest to a backup mode. OpenVINO backend supports 3 backup modes: INT8_SYM, INT8_ASYM, and NONE, which retains the original floating-point precision of the model weights. Backup mode is supported only for mixed-precision weight quantization.