Small updates to the docs

Signed-off-by: Martin Hickey <[email protected]>

Author: hickeyma

.spellcheck-en-custom.txt

@@ -50,6 +50,7 @@ lossy
 LSTM
 matmul
 matmuls
+matplotlib
 maxperCh
 maxpertoken
 Miniforge

README.md

@@ -10,7 +10,7 @@
 
 ## Introduction
 
-FMS Model Optimizer is a framework for developing reduced precision neural network models. Quantization techniques, such as [quantization-aware-training (QAT)](https://arxiv.org/abs/2407.11062), [post-training quantization (PTQ)](https://arxiv.org/abs/2102.05426), and several other optimization techniques on popular deep learning workloads are supported.
+FMS Model Optimizer is a framework for developing reduced precision neural network models. [Quantization](https://www.ibm.com/think/topics/quantization) techniques, such as [quantization-aware-training (QAT)](https://arxiv.org/abs/2407.11062), [post-training quantization (PTQ)](https://arxiv.org/abs/2102.05426), and several other optimization techniques on popular deep learning workloads are supported.
 
 ## Highlights
 
@@ -37,10 +37,11 @@ FMS Model Optimizer is a framework for developing reduced precision neural netwo
 
 1. **🐧 Linux system with Nvidia GPU (V100/A100/H100)**
 2. Python 3.9 to Python 3.11
+
     📋 Python 3.12 is currently not supported due to PyTorch Dynamo constraint
 3. CUDA >=12
 
-*Optional packages based on optimization functionalities required:*
+*Optional packages based on optimization functionality required:*
 
 - **GPTQ** is a popular compression method for LLMs: 
     - [auto_gptq](https://pypi.org/project/auto-gptq/) or build from [source](https://github.com/AutoGPTQ/AutoGPTQ)
@@ -53,15 +54,16 @@ FMS Model Optimizer is a framework for developing reduced precision neural netwo
     - Nvidia H100 family or higher
     - [llm-compressor](https://github.com/vllm-project/llm-compressor)
 - To enable compute graph plotting function (mostly for troubleshooting purpose):
+    - [matplotlib](https://matplotlib.org/)
     - [graphviz](https://graphviz.org/)
     - [pygraphviz](https://pygraphviz.github.io/)
 
 > [!NOTE]
-> PyTorch version should be < 2.4 if you would like to experiment deployment with external INT8 kernel.
+> PyTorch version should be < 2.5 if you would like to experiment deployment with external INT8 kernel.
 
 ### Installation
 
-We recommend using a Python virtual environment with Python 3.10+. Here is how to setup a virtual environment using [Python venv](https://docs.python.org/3/library/venv.html):
+We recommend using a Python virtual environment with Python 3.9+. Here is how to setup a virtual environment using [Python venv](https://docs.python.org/3/library/venv.html):
 
 ```
 python3 -m venv fms_mo_venv

examples/FP8_QUANT/README.md

@@ -10,7 +10,7 @@ This is an example of mature FP8, which under the hood leverages some functional
 ## Requirements
 
 - [FMS Model Optimizer requirements](../../README.md#requirements)
-- Nvidia A100 family or higher
+- Nvidia H100 family or higher
 - The [llm-compressor](https://github.com/vllm-project/llm-compressor) library can be installed using pip:
 
     ```bash