Use PrecompileTools.jl

### Motivation and description

Currently the startup time for using this package is quite long.
For example, running the code snippet below takes about 80s on my machine, which is 99% overhead time (the two epochs are practically instant).

To compare, a basic Flux model only takes about 6s after startup. Since in Julia 1.9 and 1.10 a lot of the compile time can be "cached away" I think we'd greatly benefit from integrating something like `PrecompileTools.jl` into the packages.

### Possible Implementation

I saw there's already a `workload.jl` file (which basically just runs all the tests) which is used for sysimg creation. Perhaps we can do something similar for the PrecompileTools.jl directive.

I can try to get a PR started in the coming days.

### Sample code
```julia
using FastAI, FastVision, Metalhead, Random
data, blocks = load(datarecipes()["mnist_png"])
idx = randperm(length(data[1]))[1:100]
data_ = (mapobs(data[1].f, data[1].data[idx]), mapobs(data[2].f, data[2].data[idx]))
task = ImageClassificationSingle(blocks)
learner = tasklearner(task, data_, backbone=ResNet(18).layers[1], callbacks=[ToGPU()])
fitonecycle!(learner, 2)
exit()
```