Update huggingface_text_full_finetune.ipynb

Author: bebechien

site/en/gemma/docs/core/huggingface_text_full_finetune.ipynb

@@ -882,7 +882,7 @@
         "id": "9RCnrmsVaadB"
       },
       "source": [
-        "If we try our original generalist prompt, we can see that the model still attempts to answer in the trained style. In this example overfitting and catastrophic forgetting are actually beneficial for the game NPC because it will begin forgetting general knowledge which might not be applicable. This is also true for other types of full fine-tuning where the goal is to restrict the output to specific data formats."
+        "If you try our original generalist prompt, you can see that the model still attempts to answer in the trained style. In this example overfitting and catastrophic forgetting are actually beneficial for the game NPC because it will begin forgetting general knowledge which might not be applicable. This is also true for other types of full fine-tuning where the goal is to restrict the output to specific data formats."
       ]
     },
     {
@@ -915,7 +915,8 @@
         "\n",
         "This tutorial covered how to full model fine-tune using TRL. Check out the following docs next:\n",
         "\n",
-        "* Learn how to [generate text with a Gemma model](https://ai.google.dev/gemma/docs/get_started).\n",
+        "* Learn how to [fine-tune Gemma for text tasks using Hugging Face Transformers](https://ai.google.dev/gemma/docs/core/huggingface_text_finetune_qlora).\n",
+        "* Learn how to [fine-tune Gemma for vision tasks using Hugging Face Transformers](https://ai.google.dev/gemma/docs/core/huggingface_vision_finetune_qlora).\n",
         "* Learn how to [deploy to Cloud Run](https://ai.google.dev/gemma/docs/integrations/google-cloud#run)"
       ]
     }