diff --git a/docs/CondaPkg.toml b/docs/CondaPkg.toml
deleted file mode 100644
index 4bd19d9..0000000
--- a/docs/CondaPkg.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-[deps]
-gdown = ""
diff --git a/docs/Project.toml b/docs/Project.toml
index 5c394d9..24eb43e 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -2,7 +2,6 @@
 AlgebraOfGraphics = "cbdf2221-f076-402e-a563-3d30da359d67"
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
-CondaPkg = "992eb4ea-22a4-4c89-a5bb-47a3300528ab"
 DataDeps = "124859b0-ceae-595e-8997-d05f6a7a8dfe"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
@@ -13,7 +12,6 @@ MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 NeuralOperators = "ea5c82af-86e5-48da-8ee1-382d6ad7af4b"
 Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
-PythonCall = "6099a3de-0909-46bc-b1f4-468b9a2dfc0d"
 Reactant = "3c362404-f566-11ee-1572-e11a4b42c853"
 Scratch = "6c6a2e73-6563-6170-7368-637461726353"
 
@@ -21,7 +19,6 @@ Scratch = "6c6a2e73-6563-6170-7368-637461726353"
 AlgebraOfGraphics = "0.10.7, 0.11, 0.12, 0.13"
 CSV = "0.10, 1.0"
 CairoMakie = "0.13, 0.14, 0.15"
-CondaPkg = "0.2.23"
 DataDeps = "0.7.13, 1.0"
 DataFrames = "1"
 Documenter = "1.7.0"
@@ -32,6 +29,5 @@ MLUtils = "0.4.4"
 NeuralOperators = "0.7"
 Optimisers = "0.4"
 Printf = "1.10, < 0.0.1, 1"
-PythonCall = "0.9.23"
 Reactant = "0.2.130"
 Scratch = "1.3.0"
diff --git a/docs/src/tutorials/burgers_deeponet.md b/docs/src/tutorials/burgers_deeponet.md
index af2cbd0..5eea26f 100644
--- a/docs/src/tutorials/burgers_deeponet.md
+++ b/docs/src/tutorials/burgers_deeponet.md
@@ -4,16 +4,14 @@
 
 ```@example burgers
 using MAT, MLUtils, Printf, DataDeps
-using PythonCall, CondaPkg # For `gdown`
-
-const gdown = pyimport("gdown")
 
 register(
     DataDep(
-        "Burgers",
+        "BurgersR10",
         """
         Burgers' equation dataset from
-        [fourier_neural_operator](https://github.com/zongyi-li/fourier_neural_operator)
+        [fourier_neural_operator](https://github.com/zongyi-li/fourier_neural_operator),
+        mirrored at [kks32/sciml-dataset](https://huggingface.co/datasets/kks32/sciml-dataset).
 
         mapping between initial conditions to the solutions at the last point of time \
         evolution in some function space.
@@ -23,16 +21,12 @@ register(
           * `a`: initial conditions u(x,0)
           * `u`: solutions u(x,t_end)
         """,
-        "https://drive.google.com/uc?id=16a8od4vidbiNR3WtaBPCSZ0T3moxjhYe",
-        "9cbbe5070556c777b1ba3bacd49da5c36ea8ed138ba51b6ee76a24b971066ecd";
-        fetch_method=(url, local_dir) -> begin
-            pyconvert(String, gdown.download(url, joinpath(local_dir, "Burgers_R10.zip")))
-        end,
-        post_fetch_method=unpack,
+        "https://huggingface.co/datasets/kks32/sciml-dataset/resolve/982685ff70965591682682dddd284d35e670ac7f/fno/burgers_data_R10.mat",
+        "d1a0456776255a4bd841dbc18951d3f468266d945d96e24ae531a12f18bb5a1a",
     ),
 )
 
-filepath = joinpath(datadep"Burgers", "burgers_data_R10.mat")
+filepath = joinpath(datadep"BurgersR10", "burgers_data_R10.mat")
 
 const N = 2048
 const Δsamples = 2^3
diff --git a/docs/src/tutorials/burgers_fno.md b/docs/src/tutorials/burgers_fno.md
index 9ad58e3..38f0350 100644
--- a/docs/src/tutorials/burgers_fno.md
+++ b/docs/src/tutorials/burgers_fno.md
@@ -4,17 +4,15 @@
 
 ```@example burgers_fno
 using DataDeps, MAT, MLUtils
-using PythonCall, CondaPkg # For `gdown`
 using Printf
 
-const gdown = pyimport("gdown")
-
 register(
     DataDep(
-        "Burgers",
+        "BurgersR10",
         """
         Burgers' equation dataset from
-        [fourier_neural_operator](https://github.com/zongyi-li/fourier_neural_operator)
+        [fourier_neural_operator](https://github.com/zongyi-li/fourier_neural_operator),
+        mirrored at [kks32/sciml-dataset](https://huggingface.co/datasets/kks32/sciml-dataset).
 
         mapping between initial conditions to the solutions at the last point of time \
         evolution in some function space.
@@ -24,16 +22,12 @@ register(
           * `a`: initial conditions u(x,0)
           * `u`: solutions u(x,t_end)
         """,
-        "https://drive.google.com/uc?id=16a8od4vidbiNR3WtaBPCSZ0T3moxjhYe",
-        "9cbbe5070556c777b1ba3bacd49da5c36ea8ed138ba51b6ee76a24b971066ecd";
-        fetch_method=(url, local_dir) -> begin
-            pyconvert(String, gdown.download(url, joinpath(local_dir, "Burgers_R10.zip")))
-        end,
-        post_fetch_method=unpack,
+        "https://huggingface.co/datasets/kks32/sciml-dataset/resolve/982685ff70965591682682dddd284d35e670ac7f/fno/burgers_data_R10.mat",
+        "d1a0456776255a4bd841dbc18951d3f468266d945d96e24ae531a12f18bb5a1a",
     ),
 )
 
-filepath = joinpath(datadep"Burgers", "burgers_data_R10.mat")
+filepath = joinpath(datadep"BurgersR10", "burgers_data_R10.mat")
 
 const N = 2048
 const Δsamples = 2^3
diff --git a/src/layers.jl b/src/layers.jl
index 1b70a44..bdf64e3 100644
--- a/src/layers.jl
+++ b/src/layers.jl
@@ -345,8 +345,10 @@ function (layer::GridEmbedding)(x::AbstractArray{T, N}, ps, st) where {T, N}
         size(x, N),
     )
 
-    # Move the CPU-built grid to the same device as x (fixes CUDA scalar indexing, #125)
-    grid = Lux.get_device(x)(grid)
+    # Place the CPU-built grid on `x`'s device (fixes CUDA scalar indexing, #125).
+    # This must not query the device at runtime: `Lux.get_device(x)` errors
+    # inside `Reactant.@compile`.
+    grid = (similar(x, eltype(grid), size(grid)) .= grid)
 
     return cat(grid, x; dims = N - 1), st
 end