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slimgroup · Apr 14, 2024 · 8e27ae4 · 8e27ae4
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diff --git a/README.md b/README.md
@@ -6,7 +6,10 @@
 
 <!-- [![][zenodo-img]][zenodo-status] -->
 
-ParametricOperators.jl is a Julia Language-based scientific library designed to facilitate the creation and manipulation of tensor operations involving large-scale data using Kronecker products. It provides an efficient and mathematically consistent way to express tensor programs and distribution in the context of machine learning.
+`ParametricOperators.jl` is a Julia Language-based scientific library designed to facilitate the creation and manipulation of tensor operations involving large-scale data using Kronecker products. It provides an efficient and mathematically consistent way to express tensor programs and distribution in the context of machine learning.
+
+> [!NOTE]  
+> [`ParametericDFNOs.jl`](https://github.com/slimgroup/ParametericDFNOs.jl/) is built on `ParametricOperators.jl`
 
 ## Features
 - <b>Kronecker Product Operations:</b> Implement tensor operations using Kronecker products for linear operators acting along multiple dimensions.
@@ -27,7 +30,7 @@ This will add `ParametricOperators.jl` as dependency to your project
 
 ## Documentation
 
-Check out the [Documentation](https://slimgroup.github.io/ParametricOperators.jl) for more or you get started by running some [examples](https://github.com/turquoisedragon2926/ParametricOperators.jl-Examples)!
+Check out the [Documentation](https://slimgroup.github.io/ParametricOperators.jl) for more or get started by running some [examples](https://github.com/turquoisedragon2926/ParametricOperators.jl-Examples)!
 
 ## Issues
 

diff --git a/docs/src/examples/3D_DConv.md b/docs/src/examples/3D_DConv.md
@@ -12,7 +12,7 @@ julia> ]
 ```
 
 !!! warning "To run on multiple GPUs"
-    If you wish to run on multiple GPUs and the below code fails to scale, make sure the GPUs are binded to different tasks. The approach we use is to unbind our GPUs on request and assign manually:
+    If you wish to run on multiple GPUs, make sure the GPUs are binded to different tasks. The approach we use is to unbind our GPUs on request and assign manually:
 
     ```julia
     CUDA.device!(rank % 4)

diff --git a/docs/src/examples/3D_DFFT.md b/docs/src/examples/3D_DFFT.md
@@ -12,7 +12,7 @@ julia> ]
 ```
 
 !!! warning "To run on multiple GPUs"
-    If you wish to run on multiple GPUs and the below code fails to scale, make sure the GPUs are binded to different tasks. The approach we use is to unbind our GPUs on request and assign manually:
+    If you wish to run on multiple GPUs, make sure the GPUs are binded to different tasks. The approach we use is to unbind our GPUs on request and assign manually:
 
     ```julia
     CUDA.device!(rank % 4)