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[Docs ]change benchmarks to version 23.3 (openvinotoolkit#22353)
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* change benchmarks to 23.3

* Update docs/articles_en/about_openvino/performance_benchmarks/performance_int8_vs_fp32.rst

* Update docs/articles_en/about_openvino/performance_benchmarks/performance_int8_vs_fp32.rst

---------

Co-authored-by: Sebastian Golebiewski <[email protected]>
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akopytko and sgolebiewski-intel authored Jan 23, 2024
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6 changes: 3 additions & 3 deletions docs/articles_en/about_openvino/performance_benchmarks.rst
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Expand Up @@ -15,7 +15,7 @@ Performance Benchmarks

openvino_docs_performance_benchmarks_faq
OpenVINO Accuracy <openvino_docs_performance_int8_vs_fp32>
Performance Data Spreadsheet (download xlsx) <https://docs.openvino.ai/2023.2/_static/benchmarks_files/OV-2023.2-Performance-Data.xlsx>
Performance Data Spreadsheet (download xlsx) <https://docs.openvino.ai/2023.2/_static/benchmarks_files/OV-2023.3-Performance-Data.xlsx>
openvino_docs_MO_DG_Getting_Performance_Numbers


Expand Down Expand Up @@ -102,14 +102,14 @@ For a listing of all platforms and configurations used for testing, refer to the

.. grid-item::

.. button-link:: _static/benchmarks_files/OV-2023.2-platform_list.pdf
.. button-link:: _static/benchmarks_files/OV-2023.3-platform_list.pdf
:color: primary
:outline:
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:material-regular:`download;1.5em` Click for Hardware Platforms [PDF]

.. button-link:: _static/benchmarks_files/OV-2023.2-system-info-detailed.xlsx
.. button-link:: _static/benchmarks_files/OV-2023.3-system-info-detailed.xlsx
:color: primary
:outline:
:expand:
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Expand Up @@ -57,6 +57,10 @@ Performance Information F.A.Q.
- Meta AI
- Auto regressive language
- 4096
* - `Mistral-7b <https://huggingface.co/mistralai/Mistral-7B-v0.1>`__
- Mistral AI
- Auto regressive language
- 4096
* - `Stable-Diffusion-V2-1 <https://huggingface.co/stabilityai/stable-diffusion-2-1>`__
- Hugginface
- Latent Diffusion Model
Expand All @@ -69,18 +73,14 @@ Performance Information F.A.Q.
- BERT-large
- question / answer
- 384
* - `deeplabv3 <https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/deeplabv3>`__
- DeepLab v3 Tf
- semantic segmentation
- 513x513
* - `efficientdet-d0 <https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/efficientdet-d0-tf>`__
- Efficientdet
- classification
- 512x512
* - `faster_rcnn_resnet50_coco <https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/faster_rcnn_resnet50_coco>`__
- Faster RCNN TF
- object detection
- 600x1024
* - `mask_rcnn_resnet50_atrous_coco <https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/mask_rcnn_resnet50_atrous_coco>`__
- Mask R-CNN ResNet 50 Atrous
- object instance segmentation
- 800x1365
* - `mobilenet-v2 <https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/mobilenet-v2-pytorch>`__
- Mobilenet V2 PyTorch
- classification
Expand All @@ -101,10 +101,6 @@ Performance Information F.A.Q.
- U-Net
- semantic segmentation
- 368x480
* - `yolo-v3 <https://https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/yolo-v3-tf>`__
- YOLO v3
- object detection
- 416x416
* - `yolo-v3-tiny <https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/yolo-v3-tiny-tf>`__
- YOLO v3 Tiny
- object detection
Expand Down Expand Up @@ -164,4 +160,3 @@ Performance Information F.A.Q.
for autonomous vehicles, where a quick response to the result of the
inference is required.


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