Update README.md

README.md

@@ -4,9 +4,13 @@ EasyDeL (Easy Deep Learning) is an open-source library designed to accelerate an
 machine learning models. This library is primarily focused on Jax/Flax and plans to offer easy and fine solutions to
 train Flax/Jax Models on the `TPU/GPU` both for Serving and Training (EasyDel will support mojo and be rewriten for mojo too)
 
-### Beta Version of EasyDel Mojo
+### EasyDel Mojo
 
-you are currenly on `mojo-beta` branch and this branch is currently developing the EasyDel for Mojo
+EasyDel Mojo differs from EasyDel in Python in significant ways. In Python, you can leverage a vast array of packages to create a mid or high-level API in no time. However, when working with Mojo, it's a different story. Here, you have to build some of the features that other Python libraries provide, such as Jax for arrays and computations. But why not import numpy, Jax, and other similar packages to Mojo and use them?
+
+There are several reasons why building packages in Mojo is more efficient than importing them from Python. Firstly, when you import packages from Python, you incur the overhead of translating and processing the Python code into Mojo code, which takes time. Secondly, the Python code may not be optimized for the Mojo runtime environment, leading to slower performance. Lastly, building packages directly in Mojo allows you to design and optimize them explicitly for the Mojo runtime environment, resulting in faster and more efficient code. With Mojo's built-in array capabilities that are 35000x faster than Python, it's time to take your coding to the next level.
+
+[Read More ...](https://github.com/erfanzar/EasyDeL/blob/main/lib/mojo/README.md)
 
 #### Note this Library needs golang to run (for some tracking stuff on TPU/GPU/CPU)