Merge pull request #2388 from Esri/jy-update-llm-ngrequest

update phrasing in llm 3rd party guide

Author: jyaistMap

guide/14-deep-learning/use_third_party_language_models_with_arcgis.ipynb

@@ -23,7 +23,7 @@
    "source": [
     "The Text Analysis toolset in the GeoAI toolbox provides a set of tools for text processing tasks, such as text classification, entity extraction, and text translation. The natural language processing (NLP) models that are created using these tools are built on language models such as BERT, RoBERTa, and T5, and large language models (LLMs), such as Mistral, to ensure high-performance text analysis.\n",
     "\n",
-    "While these prebuilt models are robust, you may need a custom NLP workflow, such as when using an LLM for standardizing addresses, performing sentiment analysis, or extracting custom entities or relationships not currently supported by the Text Analysis toolset. \n",
+    "While these prebuilt models are robust, you may need a custom NLP workflow, such as when using an LLM for translating text, performing sentiment analysis, or extracting custom entities or relationships not currently supported by the Text Analysis toolset. \n",
     "\n",
     "To meet these needs, you can integrate ArcGIS with external third-party language models. This includes open source LLMs as well as cloud-hosted, commercial LLMs accessed using a web API. Keep in mind that if you are using a web hosted LLM, the data that you are processing will be sent to the LLM provider for processing. Python developers can author a custom NLP function to integrate with external models and package their model as an Esri deep learning package (.dlpk file) for use with the following tools:\n",
     "\n",
@@ -643,7 +643,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.13.2"
   }
  },
  "nbformat": 4,