Skip to content

doc: edit AI Kit names and visibility in top-level README #74

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Mar 30, 2021
Merged

doc: edit AI Kit names and visibility in top-level README #74

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
8bb1c33
doc: edit AI Kit names and visibility in top level README
dbkinder Mar 9, 2021
be242b6
Merge branch 'master' into add-AI-Kit
dbkinder Mar 30, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
15 changes: 12 additions & 3 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,8 @@
This repository contains **links to pre-trained models, sample scripts, best practices, and step-by-step tutorials** for many popular open-source machine learning models optimized by Intel to run on Intel® Xeon® Scalable processors.

Model packages and containers for running the Model Zoo's workloads can be found at the [Intel® oneContainer Portal](https://software.intel.com/containers).
Intel Model Zoo is also bundled as a part of
[Intel® oneAPI AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html) (AI Kit).

## Purpose of the Model Zoo

Expand All @@ -16,11 +18,18 @@ For any performance and/or benchmarking information on specific Intel platforms,
## How to Use the Model Zoo

### Getting Started

- If you know what model you are interested in, or if you want to see a full list of models in the Model Zoo, start **[here](/benchmarks)**.
- For framework best practice guides, and step-by-step tutorials for some models in the Model Zoo, start **[here](/docs)**.
- With [Intel® AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html), Powered by oneAPI
- Intel Model Zoo is also released as a part of [Intel® AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html) which provides a consolidated package of Intel’s latest deep and machine learning optimizations all in one place for ease of development. Along with Model Zoo, the toolkit also includes Intel optimized versions of deep learning frameworks (Tensorflow, PyTorch) and high performing Python libraries to streamline end-to-end data science and AI workflows on Intel architectures.
- To get started you can refer to [ResNet50 FP32 Inference code sample.](https://github.com/oneapi-src/oneAPI-samples/tree/master/AI-and-Analytics/Features-and-Functionality/IntelTensorFlow_ModelZoo_Inference_with_FP32_Int8)

- AI Kit provides a consolidated package of Intel’s latest deep and machine
learning optimizations all in one place for ease of development. Along with
Model Zoo, the toolkit also includes Intel optimized versions of deep
learning frameworks (TensorFlow, PyTorch) and high performing Python libraries
to streamline end-to-end data science and AI workflows on Intel architectures.

|[Download AI Kit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit/) |[AI Kit Get Started Guide](https://software.intel.com/content/www/us/en/develop/documentation/get-started-with-ai-linux/top.html) |
|---|---|

### Directory Structure
The Model Zoo is divided into four main directories:
Expand Down