diff --git a/docs/nbdoc/consts.py b/docs/nbdoc/consts.py index ac37de068b1..42424747c0b 100644 --- a/docs/nbdoc/consts.py +++ b/docs/nbdoc/consts.py @@ -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/20230104220806/dist/rst_files/" +artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20230109220810/dist/rst_files/" blacklisted_extensions = ['.xml', '.bin'] @@ -18,8 +18,8 @@ section_names = ["Getting Started", "Convert & Optimize", # Templates binder_template = """ -This tutorial is also available as a Jupyter notebook that can be cloned directly from GitHub. -See the |installation_link| for instructions to run this tutorial locally on Windows, Linux or macOS. +This tutorial is also available as a Jupyter notebook that can be cloned directly from GitHub. +See the |installation_link| for instructions to run this tutorial locally on Windows, Linux or macOS. To run without installing anything, click the launch binder button. |binder_link| |github_link| @@ -28,7 +28,7 @@ To run without installing anything, click the launch binder button. installation guide -.. |binder_link| raw:: html +.. |binder_link| raw:: html Binder @@ -39,7 +39,7 @@ To run without installing anything, click the launch binder button. \n """ no_binder_template = """ -This tutorial is also available as a Jupyter notebook that can be cloned directly from GitHub. +This tutorial is also available as a Jupyter notebook that can be cloned directly from GitHub. See the |installation_link| for instructions to run this tutorial locally on Windows, Linux or macOS. |github_link| diff --git a/docs/tutorials.md b/docs/tutorials.md index 357342e7e9a..b4b8834ecf0 100644 --- a/docs/tutorials.md +++ b/docs/tutorials.md @@ -5,13 +5,13 @@ .. _notebook tutorials: .. meta:: - :description: A collection of Python tutorials run on Jupyter notebooks. The - tutorials explain how to use OpenVINO™ toolkit for optimized + :description: A collection of Python tutorials run on Jupyter notebooks. The + tutorials explain how to use OpenVINO™ toolkit for optimized deep learning inference. - :keywords: OpenVINO™ toolkit, Jupyter, Jupyter notebooks, tutorials, Python - API, Python, deep learning, inference, model inference, infer a - model, Binder, object detection, quantization, image - classification, speech recognition, OCR, OpenVINO IR, deep + :keywords: OpenVINO™ toolkit, Jupyter, Jupyter notebooks, tutorials, Python + API, Python, deep learning, inference, model inference, infer a + model, Binder, object detection, quantization, image + classification, speech recognition, OCR, OpenVINO IR, deep learning model, AI, neural networks .. toctree:: @@ -22,21 +22,21 @@ notebooks-installation notebooks/notebooks -This collection of Python tutorials are written for running on Jupyter notebooks. -The tutorials provide an introduction to the OpenVINO™ toolkit and explain how to -use the Python API and tools for optimized deep learning inference. You can run the -code one section at a time to see how to integrate your application with OpenVINO +This collection of Python tutorials are written for running on Jupyter notebooks. +The tutorials provide an introduction to the OpenVINO™ toolkit and explain how to +use the Python API and tools for optimized deep learning inference. You can run the +code one section at a time to see how to integrate your application with OpenVINO libraries. -Notebooks with a |binder logo| button can be run without installing anything. -Once you have found the tutorial of your interest, just click the button next to +Notebooks with a |binder logo| button can be run without installing anything. +Once you have found the tutorial of your interest, just click the button next to the name of it and `Binder `__ will start it in a new tab of a browser. Binder is a free online service with limited resources (for more information about it, see the `Additional Resources <#-additional-resources>`__ section). .. note:: - For the best performance, more control and resources, you should run the notebooks locally. - Follow the `Installation Guide `__ in order to get information + For the best performance, more control and resources, you should run the notebooks locally. + Follow the `Installation Guide `__ in order to get information on how to run and manage the notebooks on your machine. @@ -118,7 +118,7 @@ Tutorials that explain how to optimize and quantize models with OpenVINO tools. | `105-language-quantize-bert `__ | Optimize and quantize a pre-trained BERT model | +------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+ | `106-auto-device `__ | Demonstrates how to use AUTO Device | - +------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+ + +------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+ | `107-speech-recognition-quantization `__ | Optimize and quantize a pre-trained Wav2Vec2 speech model | +------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+ | `110-ct-segmentation-quantize `__ | Quantize a kidney segmentation model and show live inference | @@ -210,6 +210,9 @@ Demos that demonstrate inference on a particular model. +-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+ | `228-clip-zero-shot-image-classification `__ | Perform Zero-shot Image Classification with CLIP and OpenVINO | |n228-img1| | +-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+ + | `229-distilbert-sequence-classification `__ | Sequence Classification with OpenVINO | |n229-img1| | + +-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+ + .. raw:: html @@ -219,7 +222,7 @@ Demos that demonstrate inference on a particular model. `Model Training`_ ------------------ -Tutorials that include code to train neural networks. +Tutorials that include code to train neural networks. +-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+ @@ -409,6 +412,8 @@ Made with `contributors-img `__. :target: https://user-images.githubusercontent.com/29454499/204548693-1304ef33-c790-490d-8a8b-d5766acb6254.png .. |n228-img1| image:: https://user-images.githubusercontent.com/29454499/207795060-437b42f9-e801-4332-a91f-cc26471e5ba2.png :target: https://user-images.githubusercontent.com/29454499/207795060-437b42f9-e801-4332-a91f-cc26471e5ba2.png +.. |n229-img1| image:: https://user-images.githubusercontent.com/95271966/206130638-d9847414-357a-4c79-9ca7-76f4ae5a6d7f.png + :target: https://user-images.githubusercontent.com/95271966/206130638-d9847414-357a-4c79-9ca7-76f4ae5a6d7f.png .. |n301-img1| image:: https://user-images.githubusercontent.com/15709723/127779607-8fa34947-1c35-4260-8d04-981c41a2a2cc.png :target: https://user-images.githubusercontent.com/15709723/127779607-8fa34947-1c35-4260-8d04-981c41a2a2cc.png .. |n401-img1| image:: https://user-images.githubusercontent.com/4547501/141471665-82b28c86-cf64-4bfe-98b3-c314658f2d96.gif @@ -497,4 +502,3 @@ Made with `contributors-img `__. @endsphinxdirective -