update gpt-2 paper link

Author: rasbt

ch04/01_main-chapter-code/ch04.ipynb

@@ -106,7 +106,7 @@
    "source": [
     "- In previous chapters, we used small embedding dimensions for token inputs and outputs for ease of illustration, ensuring they fit on a single page\n",
     "- In this chapter, we consider embedding and model sizes akin to a small GPT-2 model\n",
-    "- We'll specifically code the architecture of the smallest GPT-2 model (124 million parameters), as outlined in Radford et al.'s [Language Models are Unsupervised Multitask Learners](https://www.semanticscholar.org/paper/Language-Models-are-Unsupervised-Multitask-Learners-Radford-Wu/9405cc0d6169988371b2755e573cc28650d14dfe) (note that the initial report lists it as 117M parameters, but this was later corrected in the model weight repository)\n",
+    "- We'll specifically code the architecture of the smallest GPT-2 model (124 million parameters), as outlined in Radford et al.'s [Language Models are Unsupervised Multitask Learners](https://scholar.google.com/citations?view_op=view_citation&hl=en&user=dOad5HoAAAAJ&citation_for_view=dOad5HoAAAAJ:YsMSGLbcyi4C) (note that the initial report lists it as 117M parameters, but this was later corrected in the model weight repository)\n",
     "- Chapter 6 will show how to load pretrained weights into our implementation, which will be compatible with model sizes of 345, 762, and 1542 million parameters"
    ]
   },
@@ -1271,7 +1271,7 @@
    "id": "309a3be4-c20a-4657-b4e0-77c97510b47c",
    "metadata": {},
    "source": [
-    "- Exercise: you can try the following other configurations, which are referenced in the [GPT-2 paper](https://www.semanticscholar.org/paper/Language-Models-are-Unsupervised-Multitask-Learners-Radford-Wu/9405cc0d6169988371b2755e573cc28650d14dfe), as well.\n",
+    "- Exercise: you can try the following other configurations, which are referenced in the [GPT-2 paper](https://scholar.google.com/citations?view_op=view_citation&hl=en&user=dOad5HoAAAAJ&citation_for_view=dOad5HoAAAAJ:YsMSGLbcyi4C), as well.\n",
     "\n",
     "    - **GPT2-small** (the 124M configuration we already implemented):\n",
     "        - \"emb_dim\" = 768\n",