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[DOCS] Update Interactive Tutorials (#17598)

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8
docs/get_started.md
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@ -94,10 +94,10 @@ Model Compression and Quantization
Use OpenVINO’s model compression tools to reduce your model’s latency and memory footprint while maintaining good accuracy.
* Tutorial - `OpenVINO Post-Training Model Quantization <notebooks/111-detection-quantization-with-output.html>`__
* Tutorial - `Quantization-Aware Training in TensorFlow with OpenVINO NNCF <notebooks/305-tensorflow-quantization-aware-training-with-output.html>`__
* Tutorial - `Quantization-Aware Training in PyTorch with NNCF <notebooks/302-pytorch-quantization-aware-training-with-output.html>`__
* :doc:`Model Optimization Guide <openvino_docs_model_optimization_guide>`
* Tutorial - `OpenVINO Post-Training Model Quantization <https://docs.openvino.ai/nightly/notebooks/111-yolov5-quantization-migration-with-output.html>`__
* Tutorial - `Quantization-Aware Training in TensorFlow with OpenVINO NNCF <https://docs.openvino.ai/nightly/notebooks/305-tensorflow-quantization-aware-training-with-output.html>`__
* Tutorial - `Quantization-Aware Training in PyTorch with NNCF <https://docs.openvino.ai/nightly/notebooks/302-pytorch-quantization-aware-training-with-output.html>`__
* `Model Optimization Guide <https://docs.openvino.ai/nightly/notebooks/openvino_docs_model_optimization_guide.html>`__
Automated Device Configuration
------------------------------

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docs/nbdoc/consts.py
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@ -8,7 +8,7 @@ repo_owner = "openvinotoolkit"
repo_name = "openvino_notebooks"
artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20230424220807/dist/rst_files/"
artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20230517220809/dist/rst_files/"
blacklisted_extensions = ['.xml', '.bin']

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docs/tutorials.md
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@ -119,7 +119,9 @@ Tutorials that explain how to optimize and quantize models with OpenVINO tools.
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `106-auto-device <notebooks/106-auto-device-with-output.html>`__ |br| |n106| | Demonstrates how to use AUTO Device |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `107-speech-recognition-quantization <notebooks/107-speech-recognition-quantization-with-output.html>`__ | Optimize and quantize a pre-trained Wav2Vec2 speech model |
| `107-speech-recognition-quantization <notebooks/107-speech-recognition-quantization-data2vec-with-output.html>`__ | Optimize and quantize a pre-trained Data2Vec speech model |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `107-speech-recognition-quantization <notebooks/107-speech-recognition-quantization-wav2vec2-with-output.html>`__ | Optimize and quantize a pre-trained Wav2Vec2 speech model |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `108-gpu-device <notebooks/108-gpu-device-with-output.html>`__ | Working with GPUs in OpenVINO™ |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
@ -127,7 +129,7 @@ Tutorials that explain how to optimize and quantize models with OpenVINO tools.
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `110-ct-segmentation-quantize <notebooks/110-ct-segmentation-quantize-with-output.html>`__ |br| |n110| | Quantize a kidney segmentation model and show live inference |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `111-detection-quantization <notebooks/111-detection-quantization-with-output.html>`__ |br| |n111| | Quantize an object detection model |
| `111-yolov5-quantization-migration <notebooks/111-yolov5-quantization-migration-with-output.html>`__ | Migrate YOLOv5 POT API based quantization pipeline on Neural Network Compression Framework (NNCF) |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `112-pytorch-post-training-quantization-nncf <notebooks/112-pytorch-post-training-quantization-nncf-with-output.html>`__ | Use Neural Network Compression Framework (NNCF) to quantize PyTorch model in post-training mode (without model fine-tuning) |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
@ -203,7 +205,7 @@ Demos that demonstrate inference on a particular model.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `222-vision-image-colorization <notebooks/222-vision-image-colorization-with-output.html>`__ |br| |n222| | Use pre-trained models to colorize black & white images using OpenVINO | |n222-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `223-gpt2-text-prediction <notebooks/223-gpt2-text-prediction-with-output.html>`__ | Use GPT-2 to perform text prediction on an input sequence | |n223-img1| |
| `223-text-prediction <notebooks/223-text-prediction-with-output.html>`__ | Use pretrained models to perform text prediction on an input sequence | |n223-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `224-3D-segmentation-point-clouds <notebooks/224-3D-segmentation-point-clouds-with-output.html>`__ | Process point cloud data and run 3D Part Segmentation with OpenVINO | |n224-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
@ -492,8 +494,6 @@ Made with `contributors-img <https://contrib.rocks>`__.
:target: https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F106-auto-device%2F106-auto-device.ipynb
.. |n110| image:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F110-ct-segmentation-quantize%2F110-ct-scan-live-inference.ipynb
.. |n111| image:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F111-detection-quantization%2F111-detection-quantization.ipynb
.. |n113| image:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F113-image-classification-quantization%2F113-image-classification-quantization.ipynb
.. |n114| image:: https://mybinder.org/badge_logo.svg

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tools/pot/README.md
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@ -43,7 +43,7 @@ OpenVINO provides several examples to demonstrate the POT optimization workflow:
* [Quantization of Image Classification model](https://docs.openvino.ai/latest/pot_configs_examples_README.html)
* API tutorials:
* [Quantization of Image Classification model](https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/301-tensorflow-training-openvino)
* [Quantization of Object Detection model from Model Zoo](https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/111-detection-quantization)
* [Quantization of Object Detection model from Model Zoo](https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/111-yolov5-quantization-migration)
* [Quantization of Segmentation model for medical data](https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/110-ct-segmentation-quantize)
* [Quantization of BERT for Text Classification](https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/105-language-quantize-bert)
* API examples:

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tools/pot/docs/DefaultQuantizationUsage.md
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@ -177,7 +177,7 @@ Examples
* Tutorials:
* `Quantization of Image Classification model <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/301-tensorflow-training-openvino>`__
* `Quantization of Object Detection model from Model Zoo <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/111-detection-quantization>`__
* `Quantization of Object Detection model from Model Zoo <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/111-yolov5-quantization-migration>`__
* `Quantization of Segmentation model for medical data <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/110-ct-segmentation-quantize>`__
* `Quantization of BERT for Text Classification <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/105-language-quantize-bert>`__

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tools/pot/docs/Introduction.md
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@ -39,10 +39,8 @@ try using :doc:`Quantization-aware Training <qat_introduction>` to increase its
| **Post-Training Quantization Quick Start Examples:**
| Try out these interactive Jupyter Notebook examples to learn the POT API and see post-training quantization in action:
* `Quantization of Image Classification Models with POT <notebooks/113-image-classification-quantization-with-output.html>`__.
* `Object Detection Quantization with POT <notebooks/111-detection-quantization-with-output.html>`__.
* `Quantization of Image Classification Models with POT <https://docs.openvino.ai/nightly/notebooks/113-image-classification-quantization-with-output.html>`__.
* `Object Detection Quantization with POT <https://docs.openvino.ai/nightly/notebooks/111-yolov5-quantization-migration-with-output.html>`__.
Quantizing Models with POT
#######################################

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tools/pot/openvino/tools/pot/algorithms/quantization/default/README.md
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@ -127,7 +127,7 @@ Additional Resources
Tutorials:
* `Quantization of Image Classification model <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/301-tensorflow-training-openvino>`__
* `Quantization of Object Detection model from Model Zoo <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/111-detection-quantization>`__
* `Quantization of Object Detection model from Model Zoo <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/111-yolov5-quantization-migration>`__
* `Quantization of Segmentation model for medical data <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/110-ct-segmentation-quantize>`__
* `Quantization of BERT for Text Classification <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/105-language-quantize-bert>`__

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tools/pot/openvino/tools/pot/api/samples/README.md
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@ -68,7 +68,7 @@ See the tutorials
####################
* `Quantization of Image Classification model <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/301-tensorflow-training-openvino>`__
* `Quantization of Object Detection model from Model Zoo <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/111-detection-quantization)>`__
* `Quantization of Object Detection model from Model Zoo <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/111-yolov5-quantization-migration)>`__
* `Quantization of Segmentation model for medical data <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/110-ct-segmentation-quantize>`__
* `Quantization of BERT for Text Classification <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/105-language-quantize-bert>`__