Update Zygote compat

Author: RafaelArutjunjan

.github/workflows/Documentation.yml

@@ -14,9 +14,9 @@ jobs:
       - uses: actions/checkout@v2
       - uses: julia-actions/setup-julia@latest
         with:
-          version: '1.11'
+          version: '1.10'
       - name: Install dependencies
-        run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate(); Pkg.add(["Symbolics"])'
+        run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
       - name: Build and deploy
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # If authenticating with GitHub Actions token

Project.toml

@@ -17,7 +17,7 @@ FiniteDiff = "2"
 FiniteDifferences = "0.11, 0.12"
 Reexport = "1.1, 1.2"
 ReverseDiff = "1.8, 1.9"
-Zygote = "0.6"
+Zygote = "0.6, 0.7"
 julia = "1"
 
 [extras]

docs/src/Operators.md

@@ -48,7 +48,7 @@ The exported in-place operators include `GetGrad!(), GetHess!(), GetJac!()` and
 
 ## Differentiation Backend-Agnostic Programming
 
-Essentially, the abstraction layer provided by **DerivableFunctions.jl** only requires the user to specify the "semantic" meaning of a given differentiation operation while allowing for flexible post hoc choice of backend as well as enabling symbolic pass through for the resulting computation.
+Essentially, the abstraction layer provided by [**DerivableFunctions.jl**](https://github.com/RafaelArutjunjan/DerivableFunctions.jl) only requires the user to specify the "semantic" meaning of a given differentiation operation while allowing for flexible post hoc choice of backend as well as enabling symbolic pass through for the resulting computation.
 
 For example, when calculating differential-geometric quantities such as the Riemann or Ricci tensors, which depend on complicated combinations of up to second derivatives of the components of the metric tensor, a single implementation simultaneously provides a performant numerical implementation as well as allowing for analytical insight for simple examples.
 ```julia