diff --git a/docs/Project.toml b/docs/Project.toml
index 8a10b165..1d867d5d 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -9,6 +9,7 @@ Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 MibS_jll = "118347d2-e127-56b9-9933-6abf9cc1adc1"
 QuadraticToBinary = "014a38d5-7acb-4e20-b6c0-4fe5c2344fd1"
 Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
+SCIP = "82193955-e24f-5292-bf16-6f2c5261a85f"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
@@ -17,3 +18,4 @@ HiGHS = "=1.5.1"
 Ipopt = "=1.0.2"
 MibS_jll = "=1.1.3"
 QuadraticToBinary = "=0.4.0"
+SCIP = "=0.11.12"
diff --git a/docs/src/tutorials/conic_lower.md b/docs/src/tutorials/conic_lower.md
index b68bdd38..b9e24d50 100644
--- a/docs/src/tutorials/conic_lower.md
+++ b/docs/src/tutorials/conic_lower.md
@@ -11,9 +11,9 @@ described in example 3.3 from
 ```math
 \begin{align}
     &\max_{x \in \mathbb{R}} \quad x + 3y_1 \\
-    &\st \quad 2 \leq x \leq 6\\
-    & \hspace{28pt} y(x) \in \argmin_{y\in {\mathbb{R}^3}} -y_1\\
-            & \hspace{58pt} \st \quad x + y_1 \leq 8 \\
+    &\textit{s.t.} \quad 2 \leq x \leq 6\\
+    & \hspace{28pt} y(x) \in \arg\min_{y\in {\mathbb{R}^3}} -y_1\\
+            & \hspace{58pt} \textit{s.t.} \quad x + y_1 \leq 8 \\
             & \hspace{76pt} \quad x + 4y_1 \geq 8 \\
             & \hspace{76pt}  \quad x + 2y_1 \leq 12 \\
             & \hspace{76pt}  \quad y \in {SOC}_3 \label{eq-soc}
diff --git a/docs/src/tutorials/lower_duals.jl b/docs/src/tutorials/lower_duals.jl
index 79a42bd6..2dc67ff1 100644
--- a/docs/src/tutorials/lower_duals.jl
+++ b/docs/src/tutorials/lower_duals.jl
@@ -81,7 +81,7 @@ set_lower_bound(lambda, 0.0)
 set_upper_bound(lambda, 1000.0)
 
 # Then, as before, we set a solver
-# (now SCIP with the `QuadraticToBinary.jl` wrapper) and a solution method
+# (now HiGHS with the `QuadraticToBinary.jl` wrapper) and a solution method
 # (now Fortuny-Amat and McCarl):
 
 set_optimizer(model,
@@ -107,4 +107,4 @@ for i in 1:3
     var = @variable(Upper(model), variable_type = DualOf(reserves[i]))
     push!(my_duals, var)
 end
-my_duals
+my_duals # a vector of anonimous variables
diff --git a/docs/src/tutorials/lower_duals.md b/docs/src/tutorials/lower_duals.md
index 4c544e71..8cea985b 100644
--- a/docs/src/tutorials/lower_duals.md
+++ b/docs/src/tutorials/lower_duals.md
@@ -93,7 +93,7 @@ set_upper_bound(lambda, 1000.0)
 ```
 
 Then, as before, we set a solver
-(now SCIP with the `QuadraticToBinary.jl` wrapper) and a solution method
+(now HiGHS with the `QuadraticToBinary.jl` wrapper) and a solution method
 (now Fortuny-Amat and McCarl):
 
 ```@example lower_duals
@@ -126,7 +126,7 @@ for i in 1:3
     var = @variable(Upper(model), variable_type = DualOf(reserves[i]))
     push!(my_duals, var)
 end
-my_duals
+my_duals # a vector of anonimous variables
 ```
 
 !!! info
diff --git a/docs/src/tutorials/modes.jl b/docs/src/tutorials/modes.jl
index 7d512e01..8c5a053d 100644
--- a/docs/src/tutorials/modes.jl
+++ b/docs/src/tutorials/modes.jl
@@ -57,7 +57,7 @@
 
 # We start loading all libraries needed for this example.
 
-using BilevelJuMP, QuadraticToBinary, HiGHS, Ipopt
+using BilevelJuMP, HiGHS, Ipopt, SCIP
 
 # Now we create a bilevel model with the `BilevelModel` constructor with no
 # solver nor mode specified.
@@ -96,35 +96,33 @@ objective_value(model)
 
 # ## `SOS1Mode` and `SCIP.Optimizer`
 
-# ```julia
-# set_optimizer(model, SCIP.Optimizer)
-#
-# BilevelJuMP.set_mode(model, BilevelJuMP.SOS1Mode())
-#
-# optimize!(model)
-#
-# objective_value(model)
-# ```
+set_optimizer(model, SCIP.Optimizer)
 
-# !!! info
-#     This code was not executed because SCIP might have a non-standard
-#     intallation procedure in windows.
+BilevelJuMP.set_mode(model, BilevelJuMP.SOS1Mode())
+
+optimize!(model)
+
+objective_value(model)
+
+# !!! warning
+#     SCIP requires a non-standard installation procedure in windows.
+#     See [SCIP.jl](https://github.com/scipopt/SCIP.jl#custom-installations) for
+#     more details.
 
 # ## `IndicatorMode` and `SCIP.Optimizer`
 
-# ```julia
-# set_optimizer(model, SCIP.Optimizer)
-#
-# BilevelJuMP.set_mode(model, BilevelJuMP.IndicatorMode())
-#
-# optimize!(model)
-#
-# objective_value(model)
-# ```
+set_optimizer(model, SCIP.Optimizer)
+
+BilevelJuMP.set_mode(model, BilevelJuMP.IndicatorMode())
+
+optimize!(model)
+
+objective_value(model)
 
-# !!! info
-#     This code was not executed because SCIP might have a non-standard
-#     intallation procedure in windows.
+# !!! warning
+#     SCIP requires a non-standard installation procedure in windows.
+#     See [SCIP.jl](https://github.com/scipopt/SCIP.jl#custom-installations) for
+#     more details.
 
 # ## `ProductMode` and `Ipopt.Optimizer`
 
@@ -152,20 +150,19 @@ objective_value(model)
 
 # ## `MixedMode` and `SCIP.Optimizer`
 
-# ```julia
-# set_optimizer(model, SCIP.Optimizer)
-#
-# BilevelJuMP.set_mode(model, BilevelJuMP.MixedMode(default = SOS1Mode()))
-#
-# BilevelJuMP.set_mode(c1, BilevelJuMP.IndicatorMode())
-#
-# BilevelJuMP.set_mode(c3, BilevelJuMP.SOS1Mode())
-#
-# optimize!(model)
-#
-# objective_value(model)
-# ```
-
-# !!! info
-#     This code was not executed because SCIP might have a non-standard
-#     intallation procedure in windows.
+set_optimizer(model, SCIP.Optimizer)
+
+BilevelJuMP.set_mode(model, BilevelJuMP.MixedMode(default = BilevelJuMP.SOS1Mode()))
+
+BilevelJuMP.set_mode(c1, BilevelJuMP.IndicatorMode())
+
+BilevelJuMP.set_mode(c3, BilevelJuMP.SOS1Mode())
+
+optimize!(model)
+
+objective_value(model)
+
+# !!! warning
+#     SCIP requires a non-standard installation procedure in windows.
+#     See [SCIP.jl](https://github.com/scipopt/SCIP.jl#custom-installations) for
+#     more details.
diff --git a/docs/src/tutorials/quad_to_bin.jl b/docs/src/tutorials/quad_to_bin.jl
index 0ed272c2..ff1f7c3b 100644
--- a/docs/src/tutorials/quad_to_bin.jl
+++ b/docs/src/tutorials/quad_to_bin.jl
@@ -38,15 +38,21 @@ objective_value(model)
 # However, this might lead to some solver not supporting certain functionality like SCIP.
 # In this case we need to:
 
-# ```julia
-# SOLVER = SCIP.Optimizer()
-# CACHED_SOLVER = MOI.Utilities.CachingOptimizer(
-#     MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}()), SOLVER)
-# Q_SOLVER = QuadraticToBinary.Optimizer{Float64}(CACHED_SOLVER)
-# BilevelModel(()->Q_SOLVER, mode = BilevelJuMP.ProductMode(1e-5))
-# ```
+using SCIP
+
+# !!! warning
+#     SCIP requires a non-standard installation procedure in windows.
+#     See [SCIP.jl](https://github.com/scipopt/SCIP.jl#custom-installations) for
+#     more details.
+
+SOLVER = SCIP.Optimizer()
+
+CACHED_SOLVER = MOI.Utilities.CachingOptimizer(
+    MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}()), SOLVER)
+
+Q_SOLVER = QuadraticToBinary.Optimizer{Float64}(CACHED_SOLVER)
+
+BilevelModel(()->Q_SOLVER, mode = BilevelJuMP.ProductMode(1e-5))
+
 # Note that we used `()->Q_SOLVER` instead of just `Q_SOLVER` because `BilevelModel`
 # requires as constructor and not an instance of an object.
-
-# !!! info
-#     This code was not executed to avoid excessive dependencies to build these docs.
\ No newline at end of file
diff --git a/src/moi.jl b/src/moi.jl
index cdf2dd79..b5b491a7 100644
--- a/src/moi.jl
+++ b/src/moi.jl
@@ -168,24 +168,6 @@ function accept_vector_set(
     return nothing
 end
 
-function reset!(::AbstractBilevelSolverMode)
-    return nothing
-end
-
-ignore_dual_objective(::AbstractBilevelSolverMode{T}) where {T} = true
-
-function accept_vector_set(
-    mode::AbstractBilevelSolverMode{T},
-    con::Complement,
-) where {T}
-    if con.is_vec
-        error(
-            "Set $(typeof(con.set_w_zero)) is not accepted when solution method is $(typeof(mode))",
-        )
-    end
-    return nothing
-end
-
 #=
     ComplementBoundCache used in Big-M
 =#