{"id":2612,"date":"2023-07-14T16:45:08","date_gmt":"2023-07-14T11:15:08","guid":{"rendered":"https:\/\/www.analyticsvidhya.com\/datahack-summit-2023\/?page_id=2612"},"modified":"2023-07-27T14:02:20","modified_gmt":"2023-07-27T08:32:20","slug":"demystifying-gpt-models-building-transformers-from-scratch","status":"publish","type":"page","link":"https:\/\/www.analyticsvidhya.com\/dhs-2023\/session\/demystifying-gpt-models-building-transformers-from-scratch\/","title":{"rendered":"Demystifying GPT Models: Building Transformers from Scratch"},"content":{"rendered":"<p><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch.\\n\\nThe focus will be on comprehending the architecture of transformer models, which form the basis of GPT models\\n\\nThrough practical examples, a small character-based language model will be trained, allowing participants to gain a good understanding of these models.\\n\\nThe session will systematically define and dissect the components of the transformer model, including tokenization, encoder, decoder, self-attention, multi-head self-attention, and fine-tuning.\\n\\nBy delving into these aspects, attendees will develop a scientific understanding of the intricate mechanisms and concepts behind transformer-based models.\\n\\nThe knowledge gained from this hack session will empower participants to comprehend the underlying principles of ChatGPT and similar models, paving the way for further exploration and potential advancements in natural language processing research.\\n\\nKey takeaways : \\n1. Gain an in-depth understanding of transformer models.\\n2. Learn to develop a GPT model from scratch, unraveling its inner workings.\\n3. Comprehend the architecture of transformers and their significance in natural language processing.\\n4. Train a small character-based language model to grasp the functioning of transformer models.\\n5. Explore tokenization, encoder, decoder, self-attention, and multi-head self-attention components of transformers.\\n6. Understand the concept of fine-tuning and its role in optimizing transformer models.\\n7. Acquire foundational knowledge to delve further into research and advancements in natural language processing.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:17405,&quot;3&quot;:{&quot;1&quot;:0},&quot;5&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;6&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;7&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;8&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;9&quot;:1,&quot;10&quot;:1,&quot;11&quot;:3,&quot;12&quot;:0,&quot;17&quot;:1}\">This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch.<\/span><\/p>\n<p>The focus will be on comprehending the architecture of transformer models, which form the basis of GPT models<\/p>\n<p>Through practical examples, a small character-based language model will be trained, allowing participants to gain a good understanding of these models.<\/p>\n<p>The session will systematically define and dissect the components of the transformer model, including tokenization, encoder, decoder, self-attention, multi-head self-attention, and fine-tuning.<\/p>\n<p>By delving into these aspects, attendees will develop a scientific understanding of the intricate mechanisms and concepts behind transformer-based models.<\/p>\n<p>The knowledge gained from this hack session will empower participants to comprehend the underlying principles of ChatGPT and similar models, paving the way for further exploration and potential advancements in natural language processing research.<\/p>\n<p><strong>Key takeaways :<\/strong><\/p>\n<ol>\n<li><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch.\\n\\nThe focus will be on comprehending the architecture of transformer models, which form the basis of GPT models\\n\\nThrough practical examples, a small character-based language model will be trained, allowing participants to gain a good understanding of these models.\\n\\nThe session will systematically define and dissect the components of the transformer model, including tokenization, encoder, decoder, self-attention, multi-head self-attention, and fine-tuning.\\n\\nBy delving into these aspects, attendees will develop a scientific understanding of the intricate mechanisms and concepts behind transformer-based models.\\n\\nThe knowledge gained from this hack session will empower participants to comprehend the underlying principles of ChatGPT and similar models, paving the way for further exploration and potential advancements in natural language processing research.\\n\\nKey takeaways : \\n1. Gain an in-depth understanding of transformer models.\\n2. Learn to develop a GPT model from scratch, unraveling its inner workings.\\n3. Comprehend the architecture of transformers and their significance in natural language processing.\\n4. Train a small character-based language model to grasp the functioning of transformer models.\\n5. Explore tokenization, encoder, decoder, self-attention, and multi-head self-attention components of transformers.\\n6. Understand the concept of fine-tuning and its role in optimizing transformer models.\\n7. Acquire foundational knowledge to delve further into research and advancements in natural language processing.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:17405,&quot;3&quot;:{&quot;1&quot;:0},&quot;5&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;6&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;7&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;8&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;9&quot;:1,&quot;10&quot;:1,&quot;11&quot;:3,&quot;12&quot;:0,&quot;17&quot;:1}\">Gain an in-depth understanding of transformer models.<br \/>\n<\/span><\/li>\n<li><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch.\\n\\nThe focus will be on comprehending the architecture of transformer models, which form the basis of GPT models\\n\\nThrough practical examples, a small character-based language model will be trained, allowing participants to gain a good understanding of these models.\\n\\nThe session will systematically define and dissect the components of the transformer model, including tokenization, encoder, decoder, self-attention, multi-head self-attention, and fine-tuning.\\n\\nBy delving into these aspects, attendees will develop a scientific understanding of the intricate mechanisms and concepts behind transformer-based models.\\n\\nThe knowledge gained from this hack session will empower participants to comprehend the underlying principles of ChatGPT and similar models, paving the way for further exploration and potential advancements in natural language processing research.\\n\\nKey takeaways : \\n1. Gain an in-depth understanding of transformer models.\\n2. Learn to develop a GPT model from scratch, unraveling its inner workings.\\n3. Comprehend the architecture of transformers and their significance in natural language processing.\\n4. Train a small character-based language model to grasp the functioning of transformer models.\\n5. Explore tokenization, encoder, decoder, self-attention, and multi-head self-attention components of transformers.\\n6. Understand the concept of fine-tuning and its role in optimizing transformer models.\\n7. Acquire foundational knowledge to delve further into research and advancements in natural language processing.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:17405,&quot;3&quot;:{&quot;1&quot;:0},&quot;5&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;6&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;7&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;8&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;9&quot;:1,&quot;10&quot;:1,&quot;11&quot;:3,&quot;12&quot;:0,&quot;17&quot;:1}\">Learn to develop a GPT model from scratch, unraveling its inner workings.<br \/>\n<\/span><\/li>\n<li><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch.\\n\\nThe focus will be on comprehending the architecture of transformer models, which form the basis of GPT models\\n\\nThrough practical examples, a small character-based language model will be trained, allowing participants to gain a good understanding of these models.\\n\\nThe session will systematically define and dissect the components of the transformer model, including tokenization, encoder, decoder, self-attention, multi-head self-attention, and fine-tuning.\\n\\nBy delving into these aspects, attendees will develop a scientific understanding of the intricate mechanisms and concepts behind transformer-based models.\\n\\nThe knowledge gained from this hack session will empower participants to comprehend the underlying principles of ChatGPT and similar models, paving the way for further exploration and potential advancements in natural language processing research.\\n\\nKey takeaways : \\n1. Gain an in-depth understanding of transformer models.\\n2. Learn to develop a GPT model from scratch, unraveling its inner workings.\\n3. Comprehend the architecture of transformers and their significance in natural language processing.\\n4. Train a small character-based language model to grasp the functioning of transformer models.\\n5. Explore tokenization, encoder, decoder, self-attention, and multi-head self-attention components of transformers.\\n6. Understand the concept of fine-tuning and its role in optimizing transformer models.\\n7. Acquire foundational knowledge to delve further into research and advancements in natural language processing.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:17405,&quot;3&quot;:{&quot;1&quot;:0},&quot;5&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;6&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;7&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;8&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;9&quot;:1,&quot;10&quot;:1,&quot;11&quot;:3,&quot;12&quot;:0,&quot;17&quot;:1}\">Comprehend the architecture of transformers and their significance in natural language processing.<br \/>\n<\/span><\/li>\n<li><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch.\\n\\nThe focus will be on comprehending the architecture of transformer models, which form the basis of GPT models\\n\\nThrough practical examples, a small character-based language model will be trained, allowing participants to gain a good understanding of these models.\\n\\nThe session will systematically define and dissect the components of the transformer model, including tokenization, encoder, decoder, self-attention, multi-head self-attention, and fine-tuning.\\n\\nBy delving into these aspects, attendees will develop a scientific understanding of the intricate mechanisms and concepts behind transformer-based models.\\n\\nThe knowledge gained from this hack session will empower participants to comprehend the underlying principles of ChatGPT and similar models, paving the way for further exploration and potential advancements in natural language processing research.\\n\\nKey takeaways : \\n1. Gain an in-depth understanding of transformer models.\\n2. Learn to develop a GPT model from scratch, unraveling its inner workings.\\n3. Comprehend the architecture of transformers and their significance in natural language processing.\\n4. Train a small character-based language model to grasp the functioning of transformer models.\\n5. Explore tokenization, encoder, decoder, self-attention, and multi-head self-attention components of transformers.\\n6. Understand the concept of fine-tuning and its role in optimizing transformer models.\\n7. Acquire foundational knowledge to delve further into research and advancements in natural language processing.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:17405,&quot;3&quot;:{&quot;1&quot;:0},&quot;5&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;6&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;7&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;8&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;9&quot;:1,&quot;10&quot;:1,&quot;11&quot;:3,&quot;12&quot;:0,&quot;17&quot;:1}\">Train a small character-based language model to grasp the functioning of transformer models.<\/span><\/li>\n<li><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch.\\n\\nThe focus will be on comprehending the architecture of transformer models, which form the basis of GPT models\\n\\nThrough practical examples, a small character-based language model will be trained, allowing participants to gain a good understanding of these models.\\n\\nThe session will systematically define and dissect the components of the transformer model, including tokenization, encoder, decoder, self-attention, multi-head self-attention, and fine-tuning.\\n\\nBy delving into these aspects, attendees will develop a scientific understanding of the intricate mechanisms and concepts behind transformer-based models.\\n\\nThe knowledge gained from this hack session will empower participants to comprehend the underlying principles of ChatGPT and similar models, paving the way for further exploration and potential advancements in natural language processing research.\\n\\nKey takeaways : \\n1. Gain an in-depth understanding of transformer models.\\n2. Learn to develop a GPT model from scratch, unraveling its inner workings.\\n3. Comprehend the architecture of transformers and their significance in natural language processing.\\n4. Train a small character-based language model to grasp the functioning of transformer models.\\n5. Explore tokenization, encoder, decoder, self-attention, and multi-head self-attention components of transformers.\\n6. Understand the concept of fine-tuning and its role in optimizing transformer models.\\n7. Acquire foundational knowledge to delve further into research and advancements in natural language processing.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:17405,&quot;3&quot;:{&quot;1&quot;:0},&quot;5&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;6&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;7&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;8&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;9&quot;:1,&quot;10&quot;:1,&quot;11&quot;:3,&quot;12&quot;:0,&quot;17&quot;:1}\">Explore tokenization, encoder, decoder, self-attention, and multi-head self-attention components of transformers.<br \/>\n<\/span><\/li>\n<li><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch.\\n\\nThe focus will be on comprehending the architecture of transformer models, which form the basis of GPT models\\n\\nThrough practical examples, a small character-based language model will be trained, allowing participants to gain a good understanding of these models.\\n\\nThe session will systematically define and dissect the components of the transformer model, including tokenization, encoder, decoder, self-attention, multi-head self-attention, and fine-tuning.\\n\\nBy delving into these aspects, attendees will develop a scientific understanding of the intricate mechanisms and concepts behind transformer-based models.\\n\\nThe knowledge gained from this hack session will empower participants to comprehend the underlying principles of ChatGPT and similar models, paving the way for further exploration and potential advancements in natural language processing research.\\n\\nKey takeaways : \\n1. Gain an in-depth understanding of transformer models.\\n2. Learn to develop a GPT model from scratch, unraveling its inner workings.\\n3. Comprehend the architecture of transformers and their significance in natural language processing.\\n4. Train a small character-based language model to grasp the functioning of transformer models.\\n5. Explore tokenization, encoder, decoder, self-attention, and multi-head self-attention components of transformers.\\n6. Understand the concept of fine-tuning and its role in optimizing transformer models.\\n7. Acquire foundational knowledge to delve further into research and advancements in natural language processing.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:17405,&quot;3&quot;:{&quot;1&quot;:0},&quot;5&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;6&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;7&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;8&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;9&quot;:1,&quot;10&quot;:1,&quot;11&quot;:3,&quot;12&quot;:0,&quot;17&quot;:1}\">Understand the concept of fine-tuning and its role in optimizing transformer models.<br \/>\n<\/span><\/li>\n<li><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch.\\n\\nThe focus will be on comprehending the architecture of transformer models, which form the basis of GPT models\\n\\nThrough practical examples, a small character-based language model will be trained, allowing participants to gain a good understanding of these models.\\n\\nThe session will systematically define and dissect the components of the transformer model, including tokenization, encoder, decoder, self-attention, multi-head self-attention, and fine-tuning.\\n\\nBy delving into these aspects, attendees will develop a scientific understanding of the intricate mechanisms and concepts behind transformer-based models.\\n\\nThe knowledge gained from this hack session will empower participants to comprehend the underlying principles of ChatGPT and similar models, paving the way for further exploration and potential advancements in natural language processing research.\\n\\nKey takeaways : \\n1. Gain an in-depth understanding of transformer models.\\n2. Learn to develop a GPT model from scratch, unraveling its inner workings.\\n3. Comprehend the architecture of transformers and their significance in natural language processing.\\n4. Train a small character-based language model to grasp the functioning of transformer models.\\n5. Explore tokenization, encoder, decoder, self-attention, and multi-head self-attention components of transformers.\\n6. Understand the concept of fine-tuning and its role in optimizing transformer models.\\n7. Acquire foundational knowledge to delve further into research and advancements in natural language processing.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:17405,&quot;3&quot;:{&quot;1&quot;:0},&quot;5&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;6&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;7&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;8&quot;:{&quot;1&quot;:[{&quot;1&quot;:2,&quot;2&quot;:0,&quot;5&quot;:{&quot;1&quot;:2,&quot;2&quot;:0}},{&quot;1&quot;:0,&quot;2&quot;:0,&quot;3&quot;:3},{&quot;1&quot;:1,&quot;2&quot;:0,&quot;4&quot;:1}]},&quot;9&quot;:1,&quot;10&quot;:1,&quot;11&quot;:3,&quot;12&quot;:0,&quot;17&quot;:1}\">Acquire foundational knowledge to delve further into research and advancements in natural language processing.<\/span><\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch. The focus will be on comprehending the architecture of transformer models, which form the basis of GPT models Through practical examples, a small character-based language model will be trained, allowing [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":2613,"parent":1126,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"session-details.php","meta":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Demystifying GPT Models: Building Transformers from Scratch - DataHack Summit 2023<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.analyticsvidhya.com\/dhs-2023\/session\/demystifying-gpt-models-building-transformers-from-scratch\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Demystifying GPT Models: Building Transformers from Scratch - DataHack Summit 2023\" \/>\n<meta property=\"og:description\" content=\"This session aims to provide an in-depth exploration of the inner workings of ChatGPT like models and the development of a GPT model from scratch. 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