Update transformers_llms_and_genai.ipynb

Author: bansalkanav

Module 9 - GenAI (LLMs and Prompt Engineering)/2. Intro to Transformers, LLMs and GenAI/transformers_llms_and_genai.ipynb

@@ -297,7 +297,17 @@
  " - In autoencoding task, the model adjusts its parameters to minimize the discrepancy between the input and reconstructed output, typically using a reconstruction loss such as mean squared error (MSE) or binary cross-entropy.\n",
  " - The model adjusts its parameters to minimize the discrepancy between the predicted tokens and the original tokens, typically using a cross-entropy loss.\n",
  "\n",
- "### **2. T5 (Text to Text Transfer Transformer)**\n",
+ "\n",
+ "### **2. GPT (Generative Pre-Trained Transformer)**\n",
+ "\n",
+ "1. By OpenAI - Autoregressive Language Model\n",
+ "2. **[Click Here](https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf)** to read the original paper from OpenAI - Improving Language Understanding by Generative Pre-Training.\n",
+ "3. Pretrained on: Proprietary Data (Data for which the rights of ownership are restricted so that the ability to freely distribute the is limited)\n",
+ "4. Autoregressive Language Model that uses attention to predict the next token in a sequence based on the previous tokens.\n",
+ "5. GPT relies on the decoder portion of the Transformer and ignores the encoder to become exceptionally good at generating text one token at a time.\n",
+ "\n",
+ "\n",
+ "### **3. T5 (Text to Text Transfer Transformer)**\n",
  "<img style=\"float: right;\" width=\"400\" height=\"400\" src=\"data/images/t5.jpeg\">\n",
  "\n",
  "1. In 2019, By Google - Combination of Autoencoder and Autoregressor Language Model.\n",
@@ -306,12 +316,6 @@
  "4. T5 uses both encoder and decoder of the Transformer to become highly versatile in both processing and generating text.\n",
  "5. T5 based models can generate wide range of NLP tasks, from text classification to generation.\n",
  "\n",
- "### **3. GPT (Generative Pre-Trained Transformer)**\n",
- "\n",
- "1. By OpenAI - Autoregressive Language Model.\n",
- "2. Pretrained on: Proprietary Data (Data for which the rights of ownership are restricted so that the ability to freely distribute the is limited)\n",
- "3. Autoregressive Language Model that uses attention to predict the next token in a sequence based on the previous tokens.\n",
- "4. GPT relies on the decoder portion of the Transformer and ignores the encoder to become exceptionally good at generating text one token at a time.\n",
  "\n",
  "### **4. Domain Specific LLMs**\n",
  "\n",