changes after reviews from Breck

Author: choudhary-shivani

guide/14-deep-learning/exploring_model_extensibility_for_named_entity_recognition.ipynb

@@ -167,7 +167,7 @@
    "id": "13dfe383-1507-4f73-a64f-5b50aa3e5536",
    "metadata": {},
    "source": [
-    "The model extension requires the process to be wrapped in a class that must implement the following functions:\n",
+    "The model extension requires the process be wrapped in a class that implements the following functions:\n",
     "\n",
     "- `__init__`\n",
     "\n",
@@ -551,8 +551,7 @@
     "\n",
     "Organize the files as follows:\n",
     "\n",
-    "**Create a Folder**: Create a folder and include the custom NLP function file. In our case, we will create a folder `NER_gilner_weather`. Inside this, we will place `NER_gilner_weather.emd`,the NLP function file \n",
-    "`MyCustomNER.py` and the directory containing the code of `GLiNER`.\n",
+    "**Create a Folder**: Create a folder and include the custom NLP function file. In our case, we will create a folder `NER_gilner_weather`. Inside this, we will place `NER_gilner_weather.emd`, the NLP function file `MyCustomNER.py`, and the directory containing the code of `GLiNER`.\n",
     "\n",
     "\n",
     "  ```      \n",

guide/14-deep-learning/leveraging_llms_for_real_time_decision_making_in_calamities.ipynb

@@ -210,13 +210,13 @@
    "id": "6aa80d78-407c-499f-b4b3-76a11f3bc6db",
    "metadata": {},
    "source": [
-    "The ESRI Model Definition (.emd) file will include both required and optional keys to facilitate model execution. To run **Classify Text Using Deep Learning (GeoAI)** Tool, we need to supply `InferenceFunction`, `ModelType` and `OutputField`. \n",
+    "The ESRI Model Definition (.emd) file will include both required and optional keys to facilitate model execution. To run **Classify Text Using Deep Learning (GeoAI)** Tool, we need to supply the `InferenceFunction`, `ModelType` and `OutputField`. \n",
     "\n",
     "1. `InferenceFunction`: Name of the module that contains the definition of NLP function\n",
     "2. `ModelType`: Defines the type of task. For **Classify Text Using Deep Learning (GeoAI)** Tool it will be `TextClassifier`\n",
     "3. `OutputField`: Name of the field in which contains the output\n",
     "\n",
-    "Other keys are prerogative to the Model extension author. In this case, we took liberty to state the prompt `few-shot prompting` related information - `examples` and `prompt`. We will utilize this information to construct a clear and effective prompt for the task."
+    "Other keys are prerogative of the Model extension author. In this case, we took liberty to state the prompt `few-shot prompting` related information - `examples` and `prompt`. We will utilize this information to construct a clear and effective prompt for the task."
    ]
   },
   {
@@ -278,7 +278,7 @@
    "id": "ccc1cbc9-d4dd-46bd-b6ad-578a0aa6d797",
    "metadata": {},
    "source": [
-    "Model extension requires the process to be wrapped in a class with the following functions mandatorily implemented:\n",
+    "Model extension requires the process be wrapped in a class with the following functions implemented:\n",
     "\n",
     "- `__init__`\n",
     "\n",
@@ -329,7 +329,7 @@
    "id": "f9aa02e1-fc97-428e-908e-c271b33c5670",
    "metadata": {},
    "source": [
-    "This function gathers parameters from the user for the **Classify Text Using Deep Learning (GeoAI)** Tool. The demo utilizes Llama-3 and employs `transformers` library for loading and inference. Users can customize the model’s input and output by specifying generation parameters, including `max_length` and `temperature`, to optimize the classification process."
+    "This function gathers parameters from the user for the **Classify Text Using Deep Learning (GeoAI)** Tool. The demo utilizes Llama-3 and employs the `transformers` library for loading and inference. Users can customize the model’s input and output by specifying generation parameters, including `max_length` and `temperature`, to optimize the classification process."
    ]
   },
   {
@@ -833,7 +833,7 @@
    "id": "6bfae9e3-9cd5-4608-a4d1-5ed6adbe6d36",
    "metadata": {},
    "source": [
-    "To complete a custom NLP function setup, create a ESRI Deep Learning Package (.dlpk) file. \n",
+    "To complete a custom NLP function setup, create an ESRI Deep Learning Package (.dlpk) file. \n",
     "\n",
     "Organize the files as follows:\n",
     "\n",
@@ -982,7 +982,7 @@
    "id": "ce393c87",
    "metadata": {},
    "source": [
-    "Utilizing the HarveyTweet Dataset, we successfully identified and classified tweets into critical categories such as public services and health-related information. Below are the results from the sample inputs."
+    "Utilizing the HarveyTweet Dataset, we successfully identified and classified tweets into critical categories, such as public services and health-related information. Below are the results from the sample inputs."
    ]
   },
   {