Merge branch 'main' of https://github.com/rasbt/LLMs-from-scratch

ch06/01_main-chapter-code/ch06.ipynb

@@ -2043,7 +2043,7 @@
    "metadata": {},
    "source": [
     "- We can see that the training and test set performances are practically identical\n",
-    "- However, based on the slightly lower test set performance, we can see that the model overfits the training data to a very small degree\n",
+    "- However, based on the slightly lower test set performance, we can see that the model overfits the training data to a very small degree, as well as the validation data that has been used for tweaking some of the hyperparameters, such as the learning rate\n",
     "- This is normal, however, and this gap could potentially be further reduced by increasing the model's dropout rate (`drop_rate`) or the `weight_decay` in the optimizer setting"
    ]
   },
@@ -2265,7 +2265,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,

setup/README.md

@@ -58,7 +58,7 @@ cd LLMs-from-scratch
 pip install -r requirements.txt
 ```
 
-(In contrast to Google Colab, these only need to be executed once since the Lightning AI Studion environments are persistent).
+(In contrast to Google Colab, these only need to be executed once since the Lightning AI Studio environments are persistent, even if you switch between CPU and GPU machines.)
 
 Then, navigate to the Python script or Jupyter Notebook you want to run. Optionally, you can also easily connect a GPU to accelerate the code's runtime, for example, when you are pretraining the LLM in chapter 5 or finetuning it in chapters 6 and 7.