remove old examples from doc

docs/gitbook/examples/benchmarks.md

@@ -9,11 +9,9 @@ _Avalanche_ offers significant support for _defining your own benchmarks_ (insta
 You can find **examples** related to the benchmarks here: 
 
 * [Classic MNIST benchmarks](../../../examples/all\_mnist.py): _in this simple example we show all the different ways you can use MNIST with Avalanche._
-* __[SplitCifar100 benchmark](../../../examples/lamaml\_cifar100.py): _in this example a CIFAR100 is used with its canonical split in 10 experiences, 10 classes each._
 * __[CLEAR benchmark](../../../examples/clear.py): _training and evaluating on CLEAR benchmark (RGB images)_
 * [CLEAR Linear benchmark](../../../examples/clear\_linear.py): _Training and evaluating on CLEAR benchmark (with pre-trained features)_
 * [Detection Benchmark](../../../examples/detection\_examples\_utils.py)_: about the utils you can use create a detection benchmark._
 * [Endless CL Simulator](../../../examples/endless\_cl\_sim.py)_: this example makes use of the Endless-Continual-Learning-Simulator's derived dataset scenario._
 * [Simple CTRL benchmark](../../../examples/simple\_ctrl.py): _In this example we show a simple way to use the ctrl benchmark_. 
-* [Task-Incremental Learning](../../../examples/task\_incremental.py): _this example trains on Split CIFAR10 with Naive strategy. In this example each experience has a different task label._
 * [Hugging Face integration](../../../examples/nlp.py)_: how to use Hugging Face models and datasets within Avalanche for Natural Language Processing._