factory
3 Commits
| Author | SHA256 | Message | Date | |
|---|---|---|---|---|
Ana Guerrero
|
37c4e1817a |
Accepting request 1235692 from science:machinelearning
OBS-URL: https://build.opensuse.org/request/show/1235692 OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/openvino?expand=0&rev=8 |
||
| 6f04946ce8 |
- openvino-onnx-ml-defines.patch and
openvino-remove-npu-compile-tool.patchhas been removed
as it is no longer needed in this version.
- Update to 2024.4.0
- Summary of major features and improvements
* OpenVINO 2024.6 release includes updates for enhanced
stability and improved LLM performance.
* Introduced support for Intel® Arc™ B-Series Graphics
(formerly known as Battlemage).
* Implemented optimizations to improve the inference time and
LLM performance on NPUs.
* Improved LLM performance with GenAI API optimizations and
bug fixes.
- Support Change and Deprecation Notices
* Using deprecated features and components is not advised. They
are available to enable a smooth transition to new solutions
and will be discontinued in the future. To keep using
discontinued features, you will have to revert to the last
LTS OpenVINO version supporting them. For more details, refer
to the OpenVINO Legacy Features and Components page.
* Discontinued in 2024.0:
+ Runtime components:
- Intel® Gaussian & Neural Accelerator (Intel® GNA)..
Consider using the Neural Processing Unit (NPU) for
low-powered systems like Intel® Core™ Ultra or 14th
generation and beyond.
- OpenVINO C++/C/Python 1.0 APIs (see 2023.3 API transition
guide for reference).
- All ONNX Frontend legacy API (known as ONNX_IMPORTER_API)
- 'PerfomanceMode.UNDEFINED' property as part of the
OpenVINO Python API
+ Tools:
- Deployment Manager. See installation and deployment
guides for current distribution options.
- Accuracy Checker.
- Post-Training Optimization Tool (POT). Neural Network
Compression Framework (NNCF) should be used instead.
- A Git patch for NNCF integration with
huggingface/transformers. The recommended approach is
to use huggingface/optimum-intel for applying NNCF
optimization on top of models from Hugging Face.
- Support for Apache MXNet, Caffe, and Kaldi model formats.
Conversion to ONNX may be used as a solution.
* Deprecated and to be removed in the future:
+ The macOS x86_64 debug bins will no longer be provided
with the OpenVINO toolkit, starting with OpenVINO 2024.5.
+ Python 3.8 is no longer supported, starting with
OpenVINO 2024.5.
+ As MxNet doesn’t support Python version higher than 3.8,
according to the MxNet PyPI project, it is no longer
supported by OpenVINO, either.
+ Discrete Keem Bay support is no longer supported, starting
with OpenVINO 2024.5.
+ Support for discrete devices (formerly codenamed Raptor
Lake) is no longer available for NPU.
OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/openvino?expand=0&rev=23
|
|||
| 3ac7c6a6fe |
- Update to 2024.3.0
- Summary of major features and improvements
* More Gen AI coverage and framework integrations to minimize
code changes
+ OpenVINO pre-optimized models are now available in Hugging
Face making it easier for developers to get started with
these models.
* Broader Large Language Model (LLM) support and more model
compression techniques.
+ Significant improvement in LLM performance on Intel
discrete GPUs with the addition of Multi-Head Attention
(MHA) and OneDNN enhancements.
* More portability and performance to run AI at the edge, in the
cloud, or locally.
+ Improved CPU performance when serving LLMs with the
inclusion of vLLM and continuous batching in the OpenVINO
Model Server (OVMS). vLLM is an easy-to-use open-source
library that supports efficient LLM inferencing and model
serving.
+ Ubuntu 24.04 long-term support (LTS), 64-bit (Kernel 6.8+)
(preview support)
- Support Change and Deprecation Notices
* Using deprecated features and components is not advised.
They are available to enable a smooth transition to new
solutions and will be discontinued in the future. To keep
using discontinued features, you will have to revert to the
last LTS OpenVINO version supporting them. For more details,
refer to the OpenVINO Legacy Features and Components page.
* Discontinued in 2024.0:
+ Runtime components:
- Intel® Gaussian & Neural Accelerator (Intel® GNA)..Consider
using the Neural Processing Unit (NPU) for low-powered
systems like Intel® Core™ Ultra or 14th generation
and beyond.
- OpenVINO C++/C/Python 1.0 APIs (see 2023.3 API transition
guide for reference).
- All ONNX Frontend legacy API (known as ONNX_IMPORTER_API)
- 'PerfomanceMode.UNDEFINED' property as part of the OpenVINO
Python API
+ Tools:
- Deployment Manager. See installation and deployment guides
for current distribution options.
- Accuracy Checker.
- Post-Training Optimization Tool (POT). Neural Network
Compression Framework (NNCF) should be used instead.
- A Git patch for NNCF integration with huggingface/
transformers. The recommended approach is to use
huggingface/optimum-intel for applying NNCF optimization
on top of models from Hugging Face.
- Support for Apache MXNet, Caffe, and Kaldi model formats.
Conversion to ONNX may be used as a solution.
* Deprecated and to be removed in the future:
+ The OpenVINO™ Development Tools package (pip install
openvino-dev) will be removed from installation options
and distribution channels beginning with OpenVINO 2025.0.
+ Model Optimizer will be discontinued with OpenVINO 2025.0.
Consider using the new conversion methods instead. For
more details, see the model conversion transition guide.
+ OpenVINO property Affinity API will be discontinued with
OpenVINO 2025.0. It will be replaced with CPU binding
configurations (ov::hint::enable_cpu_pinning).
+ OpenVINO Model Server components:
- “auto shape” and “auto batch size” (reshaping a model
in runtime) will be removed in the future. OpenVINO’s
dynamic shape models are recommended instead.
+ A number of notebooks have been deprecated. For an
up-to-date listing of available notebooks, refer to
the OpenVINO™ Notebook index (openvinotoolkit.github.io).
OBS-URL: https://build.opensuse.org/package/show/science:machinelearning/openvino?expand=0&rev=13
|
