Add NNCFProfiler implementation

tools/README.md

@@ -153,3 +153,17 @@ The input file should contain the following columns:
 ```shell
 python visualize_compression_results.py --input-file data/llama2_asym.csv --output-dir output_dir
 ```
+
+## Profiler
+
+The Profiler is a tool for collecting and analyzing activation statistics from OpenVINO models. It enables layer-by-layer profiling of model activations using NNCF infrastructure, making it useful for debugging quantization and compression issues, comparing model variants, and understanding activation distributions.
+
+Key features:
+
+- Collect raw activations at input and output of specific layers using regex pattern matching
+- Calculate custom statistics (min, max, mean, std, percentiles, etc.) on collected activations
+- Compare activations between two model variants (e.g., FP32 vs INT8) with built-in and custom metrics
+- Visualize activation distributions and comparison results with matplotlib
+- Extensible architecture allowing registration of custom statistics, comparators, and visualizers
+
+See [tiny_llama_profiling.ipynb](profiler/tiny_llama_profiling.ipynb) for a complete usage example demonstrating how to profile an OpenVino model, collect activation statistics, and compare FP32 vs INT8 quantized variants.