Fix typos Workflow_Interface_501_FineTuning_LLAMA2.ipynb

openfl-tutorials/experimental/Workflow_Interface_501_FineTuning_LLAMA2.ipynb

@@ -15,8 +15,8 @@
    "metadata": {},
    "source": [
     "Welcome to the introductory tutorial for the OpenFL Experimental Workflow Interface! This notebook is designed to guide you through the process of setting up your first horizontal federated learning workflow using the pre-trained Large Language Model Llama-2. The primary objectives of this tutorial are:\r\n",
-    "- Simplify the federated workflow representation\r\n",
-    "- Help users better understand the steps in federated learning\r\n",
+    "- Simplify the federated workflow representation.\r\n",
+    "- Help users better understand the steps in federated learning.\r\n",
     "- Offer a practical introduction to Large Language Models (LLMs), specifically LLAMA-2, and demonstrate how to fine-tune these models using a dataset.\r\n",
     "\r\n",
     "This tutorial serves as a basic example, and users are encouraged to adapt and expand upon it to suit their specific needs and requirements.\r\n",
@@ -43,7 +43,7 @@
    "id": "a7989e72",
    "metadata": {},
    "source": [
-    "The workflow interface is a new way of composing federated learning expermients with OpenFL. It was borne through conversations with researchers and existing users who had novel use cases that didn't quite fit the standard horizontal federated learning paradigm. "
+    "The workflow interface is a new way of composing federated learning experiments with OpenFL. It was borne through conversations with researchers and existing users who had novel use cases that didn't quite fit the standard horizontal federated learning paradigm. "
    ]
   },
   {
@@ -59,7 +59,7 @@
    "id": "4dbb89b6",
    "metadata": {},
    "source": [
-    "First we start by installing the necessary dependencies for the workflow interface"
+    "First, we start by installing the necessary dependencies for the workflow interface"
    ]
   },
   {
@@ -322,7 +322,7 @@
     "\n",
     "- `FLSpec` – Defines the flow specification. User defined flows are subclasses of this.\n",
     "- `Runtime` – Defines where the flow runs, infrastructure for task transitions (how information gets sent). The `LocalRuntime` runs the flow on a single node.\n",
-    "- `aggregator/collaborator` - placement decorators that define where the task will be assigned"
+    "- `aggregator/collaborator` - placement decorators that define where the task will be assigned."
    ]
   },
   {
@@ -503,7 +503,7 @@
    "source": [
     "You'll notice in the `FederatedFlow` definition above that there were certain attributes that the flow was not initialized with, namely the `train_loader` and `test_loader` for each of the collaborators. These are **private_attributes** that are exposed only throught he runtime. Each participant has it's own set of private attributes: a dictionary where the key is the attribute name, and the value is the object that will be made accessible through that participant's task. \n",
     "\n",
-    "Below, we segment shards of the OpenAssistant/oasst1 dataset for only **one collaborator**: Portland.However, if your GPU memory allows, you can certainly add more collaborators. Each has their own slice of the dataset that's accessible via the `train_loader` or `test_loader` attribute. Note that the private attributes are flexible, and you can choose to pass in a completely different type of object to any of the collaborators or aggregator (with an arbitrary name). These private attributes will always be filtered out of the current state when transfering from collaborator to aggregator, or vice versa. y."
+    "Below, we segment shards of the OpenAssistant/oasst1 dataset for only **one collaborator**: Portland. However, if your GPU memory allows, you can certainly add more collaborators. Each has their own slice of the dataset that's accessible via the `train_loader` or `test_loader` attribute. Note that the private attributes are flexible, and you can choose to pass in a completely different type of object to any of the collaborators or aggregator (with an arbitrary name). These private attributes will always be filtered out of the current state when transferring from collaborator to aggregator, or vice versa."
    ]
   },
   {
@@ -846,7 +846,7 @@
     "- Vertical Federated Learning\n",
     "- Model Watermarking\n",
     "- Differential Privacy\n",
-    "- And More!"
+    "- And more!"
    ]
   }
  ],