diff --git a/README.md b/README.md
index 56421b787..3218120ba 100644
--- a/README.md
+++ b/README.md
@@ -39,6 +39,8 @@ reservoir computing models. More specifically the software offers
 - 5+ reservoir states modification algorithms
 - Sparse matrix computation through
   [SparseArrays.jl](https://docs.julialang.org/en/v1/stdlib/SparseArrays/)
+- Multiple training algorithms via [LIBSVM.jl](https://github.com/JuliaML/LIBSVM.jl)
+  and [MLJLinearModels.jl](https://github.com/JuliaAI/MLJLinearModels.jl)
 
 ## Installation
 
diff --git a/docs/src/index.md b/docs/src/index.md
index 11cc3bacf..3f1cfe5aa 100644
--- a/docs/src/index.md
+++ b/docs/src/index.md
@@ -32,15 +32,32 @@ This approach can be thought as a kernel method with an explicit kernel trick.
     For faster computations on the CPU it is suggested to add `using MKL`
     to the script. For clarity's sake this library will not be indicated 
     under every example in the documentation.
+    
+!!! warn "Lux's states vs reservoir computing states"
+    
+    ReservoirComputing.jl builds on Lux.jl. As such, it inherits the model’s states `st`
+    juggling and naming. This contrasts with the naming of the internal expansions
+    of the input data, which in reservoir computing literature are also known as states.
+    Since we cannot avoid using the same name for two different things, we tried to make
+    it as explicit as possible in the documentation when we refer to one or the other.
+    If you feel that this is causing confusion in some places, please open an issue!
+
 
 ## Installation
 
 To install ReservoirComputing.jl, ensure you have Julia version 1.10 or higher.
 Follow these steps:
 
-    1. Open the Julia command line.
-    2. Enter the Pkg REPL mode by pressing ].
-    3. Type `add ReservoirComputing` and press Enter.
+1. Open the Julia command line.
+2. Enter the Pkg REPL mode by pressing ].
+3. Type `add ReservoirComputing` and press Enter.
+
+Alternatively, do:
+
+```julia
+using Pkg
+Pkg.add("ReservoirComputing")
+```
 
 For a more customized installation or to contribute to the package,
 consider cloning the repository:
@@ -61,7 +78,9 @@ or `dev` the package.
 - 5+ reservoir states modification algorithms
 - Sparse matrix computation through
   [SparseArrays.jl](https://docs.julialang.org/en/v1/stdlib/SparseArrays/)
-
+- Multiple training algorithms via [LIBSVM.jl](https://github.com/JuliaML/LIBSVM.jl)
+  and [MLJLinearModels.jl](https://github.com/JuliaAI/MLJLinearModels.jl)
+  
 ## Contributing
 
 Contributions to ReservoirComputing.jl are highly encouraged and appreciated.
diff --git a/docs/src/tutorials/scratch.md b/docs/src/tutorials/scratch.md
index 6cacd53ce..b19e66078 100644
--- a/docs/src/tutorials/scratch.md
+++ b/docs/src/tutorials/scratch.md
@@ -4,7 +4,7 @@ ReservoirComputing.jl provides utilities to build reservoir reservoir
 computing models from scratch. In this tutorial we are going to build
 an echo state network ([`ESN`](@ref)) and showcase how this custom
 implementation is equivalent to the provided model (minus some comfort
-utilities)
+utilities).
 
 ## Using provided layers: ReservoirChain, ESNCell, and LinearReadout
 
@@ -14,7 +14,7 @@ to the chain will concatenate them, and will allow the flow of the input
 data through the model.
 
 To build an ESN we also need a [`ESNCell`](@ref) to provide the ESN
-forward pass. However, the cell is stateless, so to keep the memoruy of
+forward pass. However, the cell is stateless, so to keep the memory of
 the input we need to wrap it in a [`StatefulLayer`](@ref), which saves the
 internal state in the model states `st` and feeds it to the cell in the
 next step.
diff --git a/src/layers/basic.jl b/src/layers/basic.jl
index 67ba82ab0..1b270b245 100644
--- a/src/layers/basic.jl
+++ b/src/layers/basic.jl
@@ -149,13 +149,13 @@ vectors are concatenated with `vcat` in order of appearance.
   `Collect` only when you want to control where/what is collected (or to stack
   multiple features).
 
-  ```julia
-  rc = ReservoirChain(
-          StatefulLayer(ESNCell(3 => 300)),
-          NLAT2(),
-          Collect(), # <-- collect the 300-dim reservoir after NLAT2
-          LinearReadout(300 => 3; include_collect=false) # <-- toggle off the default Collect()
-      )
+```julia
+rc = ReservoirChain(
+    StatefulLayer(ESNCell(3 => 300)),
+    NLAT2(),
+    Collect(), # <-- collect the 300-dim reservoir after NLAT2
+    LinearReadout(300 => 3; include_collect=false) # <-- toggle off the default Collect()
+)
 ```
 """
 struct Collect <: AbstractReservoirCollectionLayer end