Update on "Documentation Updates"

Summary: Updating README with better examples, updating class and api
documentation and removing the unnecessary int_mm_fused_mul option from
dynamic quant

Test Plan: python test/test.py

Reviewers:

Subscribers:

Tasks:

Tags:

[ghstack-poisoned]

Author: HDCharles

README.md

@@ -28,7 +28,7 @@ torchao                            0.0.1                   <install dir>
 Relevant APIs can be found in torchao.quantization.quant_api
 
 Note: While these techniques are designed to improve model performance, in some cases the opposite can occur.
-This is because quantization adds additional overhead to the model that is hopefully made up for by faster matmuls (for dynamic quantization) or loading weights faster (for weight-only quantization). If your matmuls are small enough or your non-quantized perf isn't bottlenecked by weight load time, these techniques may reduce performance.
+This is because quantization adds additional overhead to the model that is hopefully made up for by faster matmuls (dynamic quantization) or loading weights faster (weight-only quantization). If your matmuls are small enough or your non-quantized perf isn't bottlenecked by weight load time, these techniques may reduce performance.
 
 ### A8W8 Dynamic Quantization