[release_v2180] Release notes

ReleaseNotes.md

@@ -1,5 +1,55 @@
 # Release Notes
 
+## New in Release 2.18.0
+
+Post-training Quantization:
+
+- Breaking changes:
+  - ...
+- General:
+  - ...
+- Features:
+  - Introduced `group_size_fallback_mode` advanced weight compression parameter. This specifies how to handle nodes that do not support a default group size value. By default it is set to `GroupSizeFallbackMode.IGNORE`. This corresponds to skipping nodes that cannot be compressed with the given group size.
+  - Added support for external quantizers in the `quantize_pt2e` API, including [XNNPACKQuantizer](https://docs.pytorch.org/executorch/stable/backends-xnnpack.html#quantization) and [CoreMLQuantizer](https://docs.pytorch.org/executorch/stable/backends-coreml.html#quantization).
+- Fixes:
+  - ...
+- Improvements:
+  - Support of weight compression for models with the Rotary Positional Embedding block.
+  - Support of weight compression for models with stateful self-attention blocks.
+- Deprecations/Removals:
+  - ...
+- Tutorials:
+  - ...
+- Known issues:
+  - ...
+
+Compression-aware training:
+
+- Breaking changes:
+  - ...
+- General:
+  - ...
+- Features:
+  - ...
+- Fixes:
+  - ...
+- Improvements:
+  - ...
+- Deprecations/Removals:
+  - ...
+- Tutorials:
+  - ...
+- Known issues:
+  - ...
+
+Deprecations/Removals:
+
+- ...
+
+Requirements:
+
+- ...
+
 ## New in Release 2.17.0
 
 Post-training Quantization: