Merge pull request #899 from alan-turing-institute/update_doc_text

Update tutorial text

Author: radka-j

docs/tutorials/emulation/01_quickstart.ipynb

@@ -137,18 +137,18 @@
     "\n",
     "<summary>Model selection</summary>\n",
     "\n",
-    "By default, `AutoEmulate` will use of all the listed emulator models, but you can also specify a subset to use if you already know which kinds of models are suitable for your data.\n",
+    "By default, `AutoEmulate` will fit all the above listed emulator models, but you can also specify a subset or additional models to use if you already know which kinds of models are most suitable for your data.\n",
     "\n",
     "Specify models used by AutoEmulate with the `models` argument, for example:\n",
     "```python\n",
-    "models = [\"GaussianProcessExact\", \"RadialBasisFunctions\"]\n",
+    "models = [\"GaussianProcessRBF\", \"GaussianProcessCorrelatedRBF\", \"RadialBasisFunctions\"]\n",
     "ae = AutoEmulate(x, y, models=models)\n",
     "```\n",
     "\n",
-    "The user can also restrict the selection to just PyTorch models or probabilistis models by using the `only_pytorch` or `only_probabilistic` arguments, respectively. For example, to use only PyTorch models:\n",
+    "The user can also directly restrict the selection to just probabilistic models by using the `only_probabilistic` argument without having to list all the models individually:\n",
     "\n",
     "```python\n",
-    "ae = AutoEmulate(x, y, only_pytorch=True)\n",
+    "ae = AutoEmulate(x, y, only_probabilistic=True)\n",
     "```\n",
     "\n",
     "</details>\n",