# Transformers-for-NLP-and-Computer-Vision-3rd-Edition
**Repository Path**: michael7736_admin/Transformers-for-NLP-and-Computer-Vision-3rd-Edition
## Basic Information
- **Project Name**: Transformers-for-NLP-and-Computer-Vision-3rd-Edition
- **Description**: AI Basic
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-10-06
- **Last Updated**: 2024-10-06
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# Transformers for Natural Language Processing and Computer Vision: Take Generative AI and LLMs to the next level with Hugging Face, Google Vertex AI, ChatGPT, GPT-4V, and DALL-E 3 3rd Edition
by Denis Rothman
Last updated: September 30, 2024
This repo is continually updated and upgraded.
🚩If you see anything that doesn't run as expected, raise an issue, and we'll work on it!
📝 For details on updates and improvements, see the [Changelog](./CHANGELOG.md).
Look for 🐬 to explore *new bonus notebooks* such as OpenAI o1's reasoning models, Midjourney's API, Google Vertex AI Gemini's API, OpenAI asynchronous batch API calls!
Look for 🎏 to explore existing notebooks for the *latest model or platform releases*, such as OpenAI's latest GPT-4o and GPT-4o-mini models.
Look for 🛠 to run existing notebooks with *new dependency versions and platform API constraints and tweaks.*
# Transformers-for-NLP-and-Computer-Vision-3rd-Edition
This is the code repository for [Transformers for Natural Language Processing and Computer Vision](https://www.amazon.com/Transformers-Natural-Language-Processing-Computer/dp/1805128728/), published by Packt.
**Explore Generative AI and Large Language Models with Hugging Face, ChatGPT, GPT-4V, and DALL-E 3**
## About the book
Transformers for Natural Language Processing and Computer Vision, Third Edition, explores **Large Language Model** (**LLM**) architectures, applications, and various platforms (Hugging Face, OpenAI, and Google Vertex AI) used for **Natural Language Processing** (**NLP**) and **Computer Vision** (**CV**).
Dive into generative vision transformers and multimodal model architectures and build applications, such as image and video-to-text classifiers. Go further by combining different models and platforms and learning about AI agent replication.
## What you will learn
- Learn how to pretrain and fine-tune LLMs
- Learn how to work with multiple platforms, such as Hugging Face, OpenAI, and Google Vertex AI
- Learn about different tokenizers and the best practices for preprocessing language data
- Implement Retrieval Augmented Generation and rules bases to mitigate hallucinations
- Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP
- Create and implement cross-platform chained models, such as HuggingGPT
- Go in-depth into vision transformers with CLIP, DALL-E 2, DALL-E 3, and GPT-4V
## Table of Contents
### Chapters
1. What Are Transformers?
2. Getting Started with the Architecture of the Transformer Model
3. Emergent vs Downstream Tasks: The Unseen Depths of Transformers
4. Advancements in Translations with Google Trax, Google Translate, and Gemini
5. Diving into Fine-Tuning through BERT
6. Pretraining a Transformer from Scratch through RoBERTa
7. The Generative AI Revolution with ChatGPT
8. Fine-Tuning OpenAI GPT Models
9. Shattering the Black Box with Interpretable Tools
10. Investigating the Role of Tokenizers in Shaping Transformer Models
11. Leveraging LLM Embeddings as an Alternative to Fine-Tuning
12. Toward Syntax-Free Semantic Role Labeling with ChatGPT and GPT-4
13. Summarization with T5 and ChatGPT
14. Exploring Cutting-Edge LLMs with Vertex AI and PaLM 2
15. Guarding the Giants: Mitigating Risks in Large Language Models
16. Beyond Text: Vision Transformers in the Dawn of Revolutionary AI
17. Transcending the Image-Text Boundary with Stable Diffusion
18. Hugging Face AutoTrain: Training Vision Models without Coding
19. On the Road to Functional AGI with HuggingGPT and its Peers
20. Beyond Human-Designed Prompts with Generative Ideation
### Appendix
Appendix: Answers to the Questions
### Platforms
You can run the notebooks directly from the table below:
| Chapter | Colab | Kaggle | Gradient | StudioLab |
| :-------- | :-------- | :------- |:------- |:------- |
| | | | | |
**Part I The Foundations of Transformer Models**
**Chapter 1: What are Transformers?**
| - 🛠O_1_and_Accelerators.ipynb
- ChatGPT_Plus_writes_and_explains_AI.ipynb
|[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter01/O_1_and_Accelerators.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter01/ChatGPT_Plus_writes_and_explains_AI.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter01/O_1_and_Accelerators.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter01/ChatGPT_Plus_writes_and_explains_AI.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter01/O_1_and_Accelerators.ipynb?file=%2FChapter01%2FO_1_and_Accelerators.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter01/ChatGPT_Plus_writes_and_explains_AI.ipynb?file=%2FChapter01%2FChatGPT_Plus_writes_and_explains_AI.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter01/O_1_and_Accelerators.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter01/ChatGPT_Plus_writes_and_explains_AI.ipynb) |
**Chapter 2: Getting Started with the Architecture of the Transformer Model**
| - 🛠Multi_Head_Attention_Sub_Layer.ipynb
- positional_encoding.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter02/Multi_Head_Attention_Sub_Layer.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter02/positional_encoding.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter02/Multi_Head_Attention_Sub_Layer.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter02/positional_encoding.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter02/Multi_Head_Attention_Sub_Layer.ipynb?file=%2FChapter02%2FMulti_Head_Attention_Sub_Layer.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter02/positional_encoding.ipynb?file=%2FChapter02%2Fpositional_encoding.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter02/Multi_Head_Attention_Sub_Layer.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter02/positional_encoding.ipynb) |
**Chapter 3: Emergent vs Downstream Tasks: the Unseen Depths of Transformers**
| - From_training_to_emergence.ipynb
- Transformer_tasks_with_Hugging_Face.ipynb
|[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter03/From_training_to_emergence.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter03/Transformer_tasks_with_Hugging_Face.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter03/From_training_to_emergence.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter03/Transformer_tasks_with_Hugging_Face.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter03/From_training_to_emergence.ipynb?file=%2FChapter03%2FFrom_training_to_emergence.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter03/Transformer_tasks_with_Hugging_Face.ipynb?file=%2FChapter03%2FTransformer_tasks_with_Hugging_Face.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter03/From_training_to_emergence.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter03/Transformer_tasks_with_Hugging_Face.ipynb) |
**Chapter 4: Advancements in Translations with Google Trax, Google Translate, and Google Bard**
| - WMT_translations.ipynb
- Trax_Google_Translate.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter04/WMT_translations.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter04/Trax_Google_Translate.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter04/WMT_translations.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter04/Trax_Google_Translate.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter04/WMT_translations.ipynb?file=%2FChapter04%2FWMT_translations.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter04/Trax_Google_Translate.ipynb?file=%2FChapter04%2FTrax_Google_Translate.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter04/WMT_translations.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter04/Trax_Google_Translate.ipynb) |
**Chapter 5: Diving into Fine-Tuning through BERT**
| - BERT_Fine_Tuning_Sentence_Classification_GPU.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter05/BERT_Fine_Tuning_Sentence_Classification_GPU.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter05/BERT_Fine_Tuning_Sentence_Classification_GPU.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter05/BERT_Fine_Tuning_Sentence_Classification_GPU.ipynb?file=%2FChapter05%2FBERT_Fine_Tuning_Sentence_Classification_GPU.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter05/BERT_Fine_Tuning_Sentence_Classification_GPU.ipynb) |
**Chapter 6: Pretraining a Transformer from Scratch through RoBERTa**
| - KantaiBERT.ipynb
- 🛠 Customer_Support_for_X.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter06/KantaiBERT.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter06/Customer_Support_for_X.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter06/KantaiBERT.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter06/Customer_Support_for_X.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter06/KantaiBERT.ipynb?file=%2FChapter06%2FKantaiBERT.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter06/Customer_Support_for_X.ipynb?file=%2FChapter06%2FCustomer_Support_for_X.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter06/KantaiBERT.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter06/Customer_Support_for_X.ipynb) |
**Part II: The Rise of Suprahuman NLP**
**Chapter 7: The Generative AI Revolution with ChatGPT**
| - OpenAI_Models.ipynb
- OpenAI_GPT_4_Assistant.ipynb
- 🎏Getting_Started_GPT_4_API.ipynb(GPT-4o)
- 🎏GPT_4_RAG.ipynb(GPT-4o)
|[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_Models.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_GPT_4_Assistant.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/Getting_Started_GPT_4_API.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/GPT_4_RAG.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_Models.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_GPT_4_Assistant.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/Getting_Started_GPT_4_API.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/GPT_4_RAG.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_Models.ipynb?file=%2FChapter07%2FOpenAI_Models.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_GPT_4_Assistant.ipynb?file=%2FChapter07%2FOpenAI_GPT_4_Assistant.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/Getting_Started_GPT_4_API.ipynb?file=%2FChapter07%2FGetting_Started_GPT_4_API.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/GPT_4_RAG.ipynb?file=%2FChapter07%2FGPT_4_RAG.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_Models.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_GPT_4_Assistant.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/Getting_Started_GPT_4_API.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/GPT_4_RAG.ipynb) |
**OpenAI Reasoning models: the o1-preview API**
| - 🐬OpenAI_Reasoning_models_o1_API.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_Reasoning_models_o1_API.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_Reasoning_models_o1_API.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_Reasoning_models_o1_API.ipynb?file=%2FChapter07%2FOpenAI_Reasoning_models_o1_API.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter07/OpenAI_Reasoning_models_o1_API.ipynb) |
**Chapter 8: Fine-tuning OpenAI Models**
| - Fine_tuning_OpenAI_Models.ipynb
- 🎏Fine_tuning_GPT_4o_mini_SQuAd.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter08/Fine_tuning_OpenAI_Models.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter08/Fine_tuning_GPT_4o_mini_SQuAd.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter08/Fine_tuning_OpenAI_Models.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter08/Fine_tuning_GPT_4o_mini_SQuAd.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter08/Fine_tuning_OpenAI_Models.ipynb?file=%2FChapter08%2FFine_tuning_OpenAI_Models.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter08/Fine_tuning_OpenAI_Models.ipynb?file=%2FChapter08%2FFine_tuning_GPT_4o_mini_SQuAd.ipynb)| [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter08/Fine_tuning_OpenAI_Models.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter08/Fine_tuning_GPT_4o_mini_SQuAd.ipynb) |
**Chapter 9: Shattering the Black Box with Interpretable tools**
| - BertViz_Interactive.ipynb
- Hugging_Face_SHAP.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter09/BertViz_Interactive.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter09/Hugging_Face_SHAP.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter09/BertViz_Interactive.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter09/Hugging_Face_SHAP.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter09/BertViz_Interactive.ipynb?file=%2FChapter09%2FBertViz_Interactive.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter09/Hugging_Face_SHAP.ipynb?file=%2FChapter09%2FHugging_Face_SHAP.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter09/BertViz_Interactive.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter09/Hugging_Face_SHAP.ipynb) |
**Chapter 10: Investigating the Role of Tokenizers in Shaping Transformer Models**
| - Tokenizers.ipynb
- Sub_word_tokenizers.ipynb
- 🛠Exploring_tokenizers.ipynb
|[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Tokenizers.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Sub_word_tokenizers.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Exploring_tokenizers.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Tokenizers.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Sub_word_tokenizers.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Exploring_tokenizers.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Tokenizers.ipynb?file=%2FChapter10%2FTokenizers.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Sub_word_tokenizers.ipynb?file=%2FChapter10%2FSub_word_tokenizers.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Exploring_tokenizers.ipynb?file=%2FChapter10%2FExploring_tokenizers.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Tokenizers.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Sub_word_tokenizers.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter10/Exploring_tokenizers.ipynb) |
**Chapter 11: Leveraging LLM Embeddings as an Alternative to Fine-Tuning**
| - 🛠Embedding_with_NLKT_Gensim.ipynb
- 🎏Question_answering_with_embeddings.ipynb
- 🛠Transfer_Learning_with_Ada_Embeddings.ipynb
|[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Embedding_with_NLKT_Gensim.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Question_answering_with_embeddings.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Transfer_Learning_with_Ada_Embeddings.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Embedding_with_NLKT_Gensim.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Question_answering_with_embeddings.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Transfer_Learning_with_Ada_Embeddings.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Embedding_with_NLKT_Gensim.ipynb?file=%2FChapter11%2FEmbedding_with_NLKT_Gensim.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Question_answering_with_embeddings.ipynb?file=%2FChapter11%2FQuestion_answering_with_embeddings.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Transfer_Learning_with_Ada_Embeddings.ipynb?file=%2FChapter11%2FTransfer_Learning_with_Ada_Embeddings.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Embedding_with_NLKT_Gensim.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Question_answering_with_embeddings.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter11/Transfer_Learning_with_Ada_Embeddings.ipynb) |
**Chapter 12: Towards Syntax-Free Semantic Role Labeling with BERT and OpenAI's ChatGPT**
| - Semantic_Role_Labeling_GPT-4.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter12/Semantic_Role_Labeling_GPT-4.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter12/Semantic_Role_Labeling_GPT-4.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter12/Semantic_Role_Labeling_GPT-4.ipynb?file=%2FChapter12%2FSemantic_Role_Labeling_GPT-4.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter12/Semantic_Role_Labeling_GPT-4.ipynb) |
**Chapter 13: Summarization with T5 and ChatGPT**
| - 🛠Summerizing_Text_T5.ipynb
- Summarizing_ChatGPT.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter13/Summerizing_Text_T5.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter13/Summarizing_ChatGPT.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter13/Summerizing_Text_T5.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter13/Summarizing_ChatGPT.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter13/Summerizing_Text_T5.ipynb?file=%2FChapter13%2FSummerizing_Text_T5.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter13/Summarizing_ChatGPT.ipynb?file=%2FChapter13%2FSummarizing_ChatGPT.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter13/Summerizing_Text_T5.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter13/Summarizing_ChatGPT.ipynb) |
**Chapter 14: Exploring Cutting-Edge NLP with Google Vertex AI(PaLM and🐬Gemini)**
| - Google_Vertex_AI.ipynb
- 🐬Google_Vertex_AI_Gemini.ipynb
|[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter14/Google_Vertex_AI.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter14/Google_Vertex_AI_Gemini.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter14/Google_Vertex_AI.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter14/Google_Vertex_AI_Gemini.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter14/Google_Vertex_AI.ipynb?file=%2FChapter14%2FGoogle_Vertex_AI.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter14/Google_Vertex_AI_Gemini.ipynb?file=%2FChapter14%2FGoogle_Vertex_AI_Gemini.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter14/Google_Vertex_AI_Gemini.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter14/Google_Vertex_AI_Gemini.ipynb) |
**Chapter 15: Guarding the Giants: Mitigating Risks in Large Language Models**<
| - 🎏Auto_Big_bench.ipynb(GPT-4o,synchronous)
- 🎏Auto_Big_bench.ipynb(GPT-4o-mini,synchronous)
- 🐬GPT API Speed++ with Asynchronous Batch Calls!
- 🛠WandB_Prompts_Quickstart.ipynb
- Encoder_decoder_transformer.ipynb
- Mitigating_Generative_AI.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Auto_Big_bench.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Auto_Big_bench_GPT-4o-mini.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Asynchronous_Batch_Processing_Auto_Big_bench.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/WandB_Prompts_Quickstart.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Encoder_decoder_transformer.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Mitigating_Generative_AI.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Auto_Big_bench.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Auto_Big_bench_GPT-4o-mini.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Asynchronous_Batch_Processing_Auto_Big_bench.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/WandB_Prompts_Quickstart.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Encoder_decoder_transformer.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Mitigating_Generative_AI.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Auto_Big_bench.ipynb?file=%2FChapter15%2FAuto_Big_bench.ipynb)[](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Auto_Big_bench.ipynb?file=%2FChapter15%2FAuto_Big_bench_GPT-4o-mini.ipynb)[](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Auto_Big_bench.ipynb?file=%2FChapter15%2FAsynchronous_Batch_Processing_Auto_Big_bench.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/WandB_Prompts_Quickstart.ipynb?file=%2FChapter15%2FWandB_Prompts_Quickstart.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Encoder_decoder_transformer.ipynb?file=%2FChapter15%2FEncoder_decoder_transformer.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Mitigating_Generative_AI.ipynb?file=%2FChapter15%2FMitigating_Generative_AI.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Auto_Big_bench.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Auto_Big_bench_GPT-4o-mini.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Asynchronous_Batch_Processing_Auto_Big_bench.ipynb)[](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/WandB_Prompts_Quickstart.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Encoder_decoder_transformer.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter15/Mitigating_Generative_AI.ipynb) |
**Part III: Generative Computer Vision: A New Way to See the World**
**Chapter 16: Vision Transformers in the Dawn of Revolutionary AI**
| - ViT_CLIP.ipynb
- Getting_Started_DALL_E_API.ipynb
- 🎏GPT-4V.ipynb(GPT-4o)
|[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/ViT_CLIP.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/Getting_Started_DALL_E_API.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/GPT-4V.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/ViT_CLIP.ipynb)[](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/Getting_Started_DALL_E_API.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/GPT-4V.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/ViT_CLIP.ipynb?file=%2FChapter16%2FViT_CLIP.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/Getting_Started_DALL_E_API.ipynb?file=%2FChapter16%2FGetting_Started_DALL_E_API.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/GPT-4V.ipynb?file=%2FChapter16%2FGPT-4V.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/ViT_CLIP.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/Getting_Started_DALL_E_API.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter16/GPT-4V.ipynb) |
**Chapter 17: Transcending the Image-Text Boundary with Stable Diffusion**
| - Stable_Diffusion_Keras.ipynb
- Stable__Vision_Stability_AI.ipynb
- Stable__Vision_Stability_AI_Animation.ipynb
- Text_to_video_synthesis.ipynb
- TimeSformer.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable_Diffusion_Keras.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable__Vision_Stability_AI.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable__Vision_Stability_AI_Animation.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Text_to_video_synthesis.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/TimeSformer.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable_Diffusion_Keras.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable__Vision_Stability_AI.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable__Vision_Stability_AI_Animation.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Text_to_video_synthesis.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/TimeSformer.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable_Diffusion_Keras.ipynb?file=%2FChapter17%2FStable_Diffusion_Keras.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable__Vision_Stability_AI.ipynb?file=%2FChapter17%2FStable__Vision_Stability_AI.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable__Vision_Stability_AI_Animation.ipynb?file=%2FChapter17%2FStable__Vision_Stability_AI_Animation.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Text_to_video_synthesis.ipynb?file=%2FChapter17%2FText_to_video_synthesis.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/TimeSformer.ipynb?file=%2FChapter17%2FTimeSformer.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable_Diffusion_Keras.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable__Vision_Stability_AI.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Stable__Vision_Stability_AI_Animation.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/Text_to_video_synthesis.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter17/TimeSformer.ipynb) |
**Chapter 18: Automated Vision Transformer Training**
| - 🛠Hugging_Face_AutoTrain.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter18/Hugging_Face_AutoTrain.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter18/Hugging_Face_AutoTrain.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter18/Hugging_Face_AutoTrain.ipynb?file=%2FChapter18%2FHugging_Face_AutoTrain.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter18/Hugging_Face_AutoTrain.ipynb) |
**Chapter 19: On the Road to Functional AGI with HuggingGPT and its Peers**
| - Computer_Vision_Analysis.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter19/Computer_Vision_Analysis.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter19/Computer_Vision_Analysis.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter19/Computer_Vision_Analysis.ipynb?file=%2FChapter19%2FComputer_Vision_Analysis.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter19/Computer_Vision_Analysis.ipynb) |
**Chapter 20: Generative AI Ideation Vertex AI, Langchain, and Stable Diffusion**
| - Automated_Design.ipynb
- Midjourney_bot.ipynb
- 🎏Automated_Ideation.ipynb
- 🐬 MyMidjourney_API.ipynb
| [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Automated_Design.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Midjourney_bot.ipynb) [](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Automated_Ideation.ipynb)[](https://colab.research.google.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/MyMidjourney_API.ipynb) | [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Automated_Design.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Midjourney_bot.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Automated_Ideation.ipynb) [](https://kaggle.com/kernels/welcome?src=https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/MyMidjourney_API.ipynb) | [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Automated_Design.ipynb?file=%2FChapter20%2FAutomated_Design.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Midjourney_bot.ipynb?file=%2FChapter20%2FMidjourney_bot.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Automated_Ideation.ipynb?file=%2FChapter20%2FAutomated_Ideation.ipynb) [](https://console.paperspace.com/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/MyMidjourney_API.ipynb?file=%2FChapter20%2FMyMidjourney_API.ipynb) | [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Automated_Design.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Midjourney_bot.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/Automated_Ideation.ipynb) [](https://studiolab.sagemaker.aws/import/github/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/blob/main/Chapter20/MyMidjourney_API.ipynb) |
### Chat with this repository's Input-Augmented GPT-4 Chatbot
Chat with my custom GPT4 bot for this repository
.
> You can ask questions about this repository. You can also copy the code from the notebooks into my chat GPT and ask for explanations.
>
> This is a cutting-edge input-augmented Chatbot built on OpenAI for this GitHub repository. OpenAI requires a ChatGPT Plus subscription to explore it.
>
> *Limitations:* This is an experimental chatbot. It is dedicated to this GitHub repository and does not replace the explanations provided in the book. But you can surely have some interesting educational interactions with my GPT-4 chatbot.
### Raise an issue
> You can [create an issue](https://github.com/Denis2054/Transformers-for-NLP-and-Computer-Vision-3rd-Edition/issues) We will be glad to provide support!in this repository if you encounter one in the notebooks.
### Get my copy
> If you feel this book is for you, get your [copy](https://www.amazon.com/Transformers-Natural-Language-Processing-Computer-ebook/dp/B0CNH9V8M5/) today!
## Know more on the Discord server 
You can get more engaged on the Discord server for more latest updates and discussions in the community at [Discord](https://www.packt.link/Transformers)
## Download a free PDF 
_If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost. Simply click on the link to claim your_
[Free PDF](https://packt.link/free-ebook/9781805128724)
We also provide a PDF file that has color images of the screenshots/diagrams used in this book at [ColorImages](https://packt.link/gbp/9781805128724)
## Get to Know the Author
Denis Rothman graduated from Sorbonne University and Paris-Cité University, designing one of the first patented encoding and embedding systems and teaching at Paris-I Panthéon Sorbonne.He authored one of the first patented word encoding and AI bots/robots. He began his career delivering a Natural Language Processing (NLP) chatbot for Moët et Chandon(LVMH) and an AI tactical defense optimizer for Airbus (formerly Aerospatiale).
Denis then authored an AI optimizer for IBM and luxury brands, leading to an Advanced Planning and Scheduling (APS) solution used worldwide.
[LinkedIn](https://www.linkedin.com/in/denis-rothman-0b034043/)