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				@@ -1,6 +1,38 @@ 
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				  "cells": [ 
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				   { 
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				+   "cell_type": "markdown", 
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				+   "id": "d0b5beda", 
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				+   "metadata": {}, 
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				+   "source": [ 
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				+    "## Notebook 3: Transcript Re-writer\n", 
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				+    "\n", 
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				+    "In the previouse notebook, we got a great podcast transcript using the raw file we have uploaded earlier. \n", 
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				+    "\n", 
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				+    "In this one, we will use `Llama-3.1-8B-Instruct` model to re-write the output from previous pipeline and make it more dramatic or realistic." 
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				+   ] 
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				+  }, 
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				+  { 
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				+   "cell_type": "markdown", 
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				+   "id": "fdc3d32a", 
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				+   "metadata": {}, 
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				+   "source": [ 
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				+    "We will again set the `SYSTEM_PROMPT` and remind the model of its task. \n", 
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				+    "\n", 
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				+    "Note: We can even prompt the model like so to encourage creativity:\n", 
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				+    "\n", 
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				+    "> Your job is to use the podcast transcript written below to re-write it for an AI Text-To-Speech Pipeline. A very dumb AI had written this so you have to step up for your kind.\n" 
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				+   ] 
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				+  }, 
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				+  { 
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				+   "cell_type": "markdown", 
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				+   "id": "c32c0d85", 
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				+   "metadata": {}, 
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				+   "source": [ 
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				+    "Note: We will prompt the model to return a list of Tuples to make our life easy in the next stage of using these for Text To Speech Generation" 
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				+   ] 
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				+  }, 
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				+  { 
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				    "cell_type": "code", 
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				    "execution_count": 1, 
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				    "id": "8568b77b-7504-4783-952a-3695737732b7", 
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				@@ -52,6 +84,14 @@ 
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				    ] 
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				   }, 
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				   { 
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				+   "cell_type": "markdown", 
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				+   "id": "8ee70bee", 
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				+   "metadata": {}, 
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				+   "source": [ 
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				+    "This time we will use the smaller 8B model" 
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				+   ] 
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				+  }, 
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				+  { 
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				    "cell_type": "code", 
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				    "execution_count": 2, 
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				    "id": "ebef919a-9bc7-4992-b6ff-cd66e4cb7703", 
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				@@ -62,6 +102,14 @@ 
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				    ] 
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				   }, 
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				   { 
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				+   "cell_type": "markdown", 
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				+   "id": "f7bc794b", 
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				+   "metadata": {}, 
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				+   "source": [ 
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				+    "Let's import the necessary libraries" 
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				+   ] 
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				+  }, 
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				+  { 
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				    "cell_type": "code", 
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				    "execution_count": 3, 
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				    "id": "de29b1fd-5b3f-458c-a2e4-e0341e8297ed", 
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				@@ -80,6 +128,16 @@ 
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				    ] 
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				   }, 
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				   { 
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				+   "cell_type": "markdown", 
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				+   "id": "8020c39c", 
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				+   "metadata": {}, 
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				+   "source": [ 
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				+    "We will load in the pickle file saved from previous notebook\n", 
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				+    "\n", 
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				+    "This time the `INPUT_PROMPT` to the model will be the output from the previous stage" 
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				+   ] 
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				+  }, 
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				+  { 
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				    "cell_type": "code", 
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				    "execution_count": 4, 
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				    "id": "4b5d2c0e-a073-46c0-8de7-0746e2b05956", 
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				@@ -93,6 +151,14 @@ 
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				    ] 
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				   }, 
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				   { 
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				+   "cell_type": "markdown", 
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				+   "id": "c4461926", 
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				+   "metadata": {}, 
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				+   "source": [ 
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				+    "We can again use Hugging Face `pipeline` method to generate text from the model" 
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				+   ] 
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				+  }, 
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				+  { 
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				    "cell_type": "code", 
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				    "execution_count": null, 
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				    "id": "eec210df-a568-4eda-a72d-a4d92d59f022", 
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				@@ -141,6 +207,14 @@ 
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				    ] 
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				   }, 
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				   { 
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				+   "cell_type": "markdown", 
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				+   "id": "612a27e0", 
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				+   "metadata": {}, 
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				+   "source": [ 
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				+    "We can verify the output from the model" 
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				+   ] 
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				+  }, 
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				+  { 
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				    "cell_type": "code", 
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				    "execution_count": null, 
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				    "id": "b8632442-f9ce-4f63-82bd-bb5238a23dc1", 
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				@@ -161,6 +235,14 @@ 
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				    ] 
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				   }, 
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				   { 
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				+   "cell_type": "markdown", 
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				+   "id": "d495a957", 
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				+   "metadata": {}, 
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				+   "source": [ 
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				+    "Let's save the output as a pickle file to be used in Notebook 4" 
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				+   ] 
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				+  }, 
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				+  { 
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				    "cell_type": "code", 
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				    "execution_count": null, 
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				    "id": "281d3db7-5bfa-4143-9d4f-db87f22870c8", 
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