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42 changes: 42 additions & 0 deletions ReleaseNotes.md
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# Release Notes

## New in Release 2.12.0

Post-training Quantization:

- Features:
- (OpenVINO, PyTorch, ONNX) Excluded comparison operators from the quantization scope for `nncf.ModelType.TRANSFORMER`.
- (OpenVINO, PyTorch) Changed the representation of symmetrically quantized weights from an unsigned integer with a fixed zero-point to a signed data type without a zero-point in the `nncf.compress_weights()` method.
- (OpenVINO) Extended patterns support of the AWQ algorithm as part of `nncf.compress_weights()`. This allows apply AWQ for the wider scope of the models.
- (OpenVINO) Introduced `nncf.CompressWeightsMode.E2M1` as the new precision for the `mode` option of `nncf.compress_weights()`.
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- (OpenVINO) Added support for models with BF16 precision in the `nncf.quantize()` method.
- (PyTorch) Added quantization support for the `torch.addmm`.
- (PyTorch) Added quantization support for the `torch.nn.functional.scaled_dot_product_attention`.
- Fixes:
- (OpenVINO, PyTorch, ONNX) Fixed Fast-/BiasCorrection algorithms with correct support of transposed MatMul layers.
- (OpenVINO) Fixed `nncf.IgnoredScope()` functionality for models with If operation.
- (OpenVINO) Fixed patterns with PReLU operations.
- Fixed runtime error while importing NNCF without Matplotlib package.
- Improvements:
- Reduced the amount of memory required for applying `nncf.compress_weights()` to OpenVINO models.
- Improved logging in case of the not empty `nncf.IgnoredScope()`.
- Tutorials:
- [Post-Training Optimization of Stable Audio Open Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/stable-audio/stable-audio.ipynb)
- [Post-Training Optimization of Phi3-Vision Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/phi-3-vision/phi-3-vision.ipynb)
- [Post-Training Optimization of MiniCPM-V2 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/minicpm-v-multimodal-chatbot/minicpm-v-multimodal-chatbot.ipynb)
- [Post-Training Optimization of Jina CLIP Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/jina-clip/jina-clip.ipynb)
- [Post-Training Optimization of Stable Diffusion v3 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/stable-diffusion-v3/stable-diffusion-v3.ipynb)
- [Post-Training Optimization of HunyuanDIT Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/hunyuan-dit-image-generation/hunyuan-dit-image-generation.ipynb)
- [Post-Training Optimization of DDColor Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/ddcolor-image-colorization/ddcolor-image-colorization.ipynb)
- [Post-Training Optimization of DynamiCrafter Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/dynamicrafter-animating-images/dynamicrafter-animating-images.ipynb)
- [Post-Training Optimization of DepthAnythingV2 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/depth-anything/depth-anything-v2.ipynb)
- [Post-Training Optimization of Kosmos-2 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/kosmos2-multimodal-large-language-model/kosmos2-multimodal-large-language-model.ipynb)

Compression-aware training:

- Fixes:
- (PyTorch) Fixed issue with wrapping for operator without patched state.

Requirements:

- Updated Tensorflow (2.15) version. This version requires Python 3.9-3.11.
- Added NumPy 2.0 support.

## New in Release 2.11.0

Post-training Quantization:
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