add supported frameworks to readme

README.md

@@ -64,7 +64,6 @@ Ivy is an open-source machine learning framework that enables you to:
 
 - Convert ML models, tools and libraries between frameworks while maintaining complete functionality using `ivy.transpile`
 - Create optimized graph-based models and functions in any native framework (PyTorch, TensorFlow, etc..) with `ivy.trace_graph`
-- Use your ML models or functions in any framework using a graph-tracing approach with `ivy.graph_transpile` *(deprecated)*
 
 <div style="display: block;" align="center">
     <div>
@@ -132,6 +131,20 @@ tutorials to do so are available!
 
 <br>
 
+# Supported Frameworks
+
+These are the frameworks that `ivy.transpile` currently supports conversions from and to.
+We're working hard on adding support for more frameworks, let us know on [Discord](https://discord.gg/uYRmyPxMQq) if there are source/target frameworks that would be useful for you!
+
+| Framework  | Source | Target |
+|------------|:------:|:------:|
+| PyTorch    |   ✅   |   🚧   |
+| TensorFlow |   🚧   |   ✅   |
+| JAX        |   🚧   |   🚧   |
+| NumPy      |   🚧   |   🚧   |
+
+<br>
+
 # Getting started
 
 - [Docs](https://ivy.dev/docs)

docs/overview/design/ivy_as_a_transpiler.rst

@@ -13,7 +13,7 @@ Here, we explain the Ivy's source-to-source transpiler and computational graph t
 +-------------+-+--------+--------+
 | TensorFlow  | | 🚧     | ✅     |
 +-------------+-+--------+--------+
-| JAX         | | 🚧     | ✅     |
+| JAX         | | 🚧     | 🚧     |
 +-------------+-+--------+--------+
 | NumPy       | | 🚧     | 🚧     |
 +-------------+-+--------+--------+