Update Part_1_Data_Preperation.ipynb

recipes/quickstart/Multi-Modal-RAG/notebooks/Part_1_Data_Preperation.ipynb

@@ -27,11 +27,7 @@
    "source": [
     "### Removing Corrupt Images\n",
     "\n",
-    "Like everything in the real world, all datasets come with some corruption. Thankfully here we can fix it ourselves. \n",
-    "\n",
-    "Obviously this is a great first step to check. Unfortunately, the author of the notebook realised there are corrupt images after crashing a GPU script 8 hours later. \n",
-    "\n",
-    "We can now use this hindsight to act like smart data scientists and fix this first. "
+    "We will start by cleaning up the dataset first and checking for any corrupt images. "
    ]
   },
   {
@@ -72,7 +68,7 @@
     "\n",
     "- PIL: For handling images to be passed to our Llama model\n",
     "- Huggingface Tranformers: For running the model\n",
-    "- Concurrent Library: To look smart when doing OS stuff by using concurrency :) "
+    "- Concurrent Library: To clean up faster"
    ]
   },
   {
@@ -107,9 +103,7 @@
    "source": [
     "#### Clean Corrupt Images\n",
     "\n",
-    "Cleaning corruption is a task for AGI but we can handle the corrupt images in our dataset for now with some concurrency for fast checking. \n",
-    "\n",
-    "This takes a few moments so it might be a good idea to take a small break and socialise for a good change. "
+    "This might take a few moments since we have 5000 images in our dataset."
    ]
   },
   {
@@ -366,8 +360,6 @@
    "source": [
     "## EDA\n",
     "\n",
-    "Now that we got rid of corruption we can proceed to building a great society with checking our dataset :) \n",
-    "\n",
     "Let's start by double-checking any empty values"
    ]
   },
@@ -612,7 +604,7 @@
    "id": "1cc50c67",
    "metadata": {},
    "source": [
-    "If we had more ~~prompts~~ time, this would be a fancier plot but for now let's take a look at the distribution skew to understand what's in our dataset:"
+    "Let's take a look at the distribution skew to understand what's in our dataset:"
    ]
   },
   {
@@ -813,7 +805,7 @@
    "id": "c2793936",
    "metadata": {},
    "source": [
-    "For once, lack of fashion knowledge is useful-we can reduce our work by creating less categories. Nicely organised just like an coder's wardrobe"
+    "For once, lack of fashion knowledge is useful-we can reduce our work by creating less categories."
    ]
   },
   {
@@ -1013,7 +1005,7 @@
     "\n",
     "At this stage, we are ready to start labelling the images using Llama-3.2 models. We will use 11B here for testing. \n",
     "\n",
-    "For our rich readers, we suggest testing 90B as an assignment. Although you will find that 11B is a great candidate for this model. \n",
+    "We suggest testing 90B as an assignment. Although you will find that 11B is a great candidate for this model. \n",
     "\n",
     "Read more about the model capabilites [here](https://www.llama.com/docs/how-to-guides/vision-capabilities/)"
    ]
@@ -1123,9 +1115,7 @@
    "source": [
     "#### Labelling Prompt\n",
     "\n",
-    "For anyone who feels strongly about Prompt Engineering-this section is for you. This requires exercising more prompt engineering techniques as suggested below.\n",
-    "\n",
-    "Suggested approach:\n",
+    "We did a few sample runs to arrive on the prompt below: \n",
     "\n",
     "- Run a simple prompt on an image\n",
     "- See output and iterate\n",
@@ -1220,9 +1210,9 @@
    "source": [
     "### Testing Labelling Script\n",
     "\n",
-    "The results from labelling above look promising, we can now start building a script skeleton in the notebook (don't worry script kiddies we will leave the notebook soon). \n",
+    "The results from labelling above look promising, we can now start building a script skeleton in the notebook to test our label logic.\n",
     "\n",
-    "Let's test our approach for first 50 images after which we can let this run on multi-GPUs in a script:"
+    "Let's test our approach for first 50 images after which we can let this run on multi-GPUs in a script. Remember, Llama-3.2 models can only look at one image at once."
    ]
   },
   {
@@ -1326,7 +1316,7 @@
    "id": "fcf2a894",
    "metadata": {},
    "source": [
-    "It's always a great idea to ~~have trust issues~~ validate LLM outputs, we can check our labels here:"
+    "It's always a great idea to validate LLM outputs, we can check our labels here:"
    ]
   },
   {