https://github.com/aishwaryanr/awesome-generative-ai-guide
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
https://github.com/aishwaryanr/awesome-generative-ai-guide
List: awesome-generative-ai-guide
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A one stop repository for generative AI research updates, interview resources, notebooks and much more!
- Host: GitHub
- URL: https://github.com/aishwaryanr/awesome-generative-ai-guide
- Owner: aishwaryanr
- License: mit
- Created: 2024-02-06T18:14:14.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-10T21:28:35.000Z (over 1 year ago)
- Last Synced: 2024-04-11T18:57:15.695Z (over 1 year ago)
- Topics: awesome, awesome-list, generative-ai, interview-questions, large-language-models, llms, notebook-jupyter, vision-and-language
- Homepage: https://www.linkedin.com/in/areganti/
- Size: 22.3 MB
- Stars: 3,614
- Watchers: 94
- Forks: 697
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# :star: :bookmark: awesome-generative-ai-guide
Generative AI is experiencing rapid growth, and this repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more!
Explore the following resources:
1. [Monthly Best GenAI Papers List](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#star-best-genai-papers-list-january-2024)
2. [GenAI Interview Resources](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#computer-interview-prep)
3. [Applied LLMs Mastery 2024 (created by Aishwarya Naresh Reganti) course material](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#ongoing-applied-llms-mastery-2024)
4. [Generative AI Genius 2024 (created by Aishwarya Naresh Reganti) course material](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/generative_ai_genius/README.md)
5. [List of all GenAI-related free courses (over 90 listed)](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#book-list-of-free-genai-courses)
6. [List of code repositories/notebooks for developing generative AI applications](https://github.com/aishwaryanr/awesome-generative-ai-guide?tab=readme-ov-file#notebook-code-notebooks)
We'll be updating this repository regularly, so keep an eye out for the latest additions!
Happy Learning!
---
## :star: Top AI Tools List
Discover our favorite AI tools spanning every layer of AI application development. Click [here](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/our_favourite_ai_tools.md) to learn more.
---
## :speaker: Announcements
- Applied LLMs Mastery full course content has been released!!! ([Click Here](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024))
- 5-day roadmap to learn LLM foundations out now! ([Click Here](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/genai_roadmap.md))
- 60 Common GenAI Interview Questions out now! ([Click Here](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/interview_prep/60_gen_ai_questions.md))
- ICLR 2024 paper summaries ([Click Here](https://areganti.notion.site/06f0d4fe46a94d62bff2ae001cfec22c?v=d501ca62e4b745768385d698f173ae14))
- List of free GenAI courses ([Click Here](https://github.com/aishwaryanr/awesome-generative-ai-guide#book-list-of-free-genai-courses))
- Generative AI resources and roadmaps
- [3-day RAG roadmap](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/RAG_roadmap.md)
- [5-day LLM foundations roadmap](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/genai_roadmap.md)
- [5-day LLM agents roadmap](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/agents_roadmap.md)
- [Agents 101 guide](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/agents_101_guide.md)
- [Introduction to MM LLMs](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/mm_llms_guide.md)
- [LLM Lingo Series: Commonly used LLM terms and their easy-to-understand definitions](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/resources/llm_lingo)
---
## :mortar_board: Courses
#### [Ongoing] Applied LLMs Mastery 2024
Join 1000+ students on this 10-week adventure as we delve into the application of LLMs across a variety of use cases
#### [Link](https://areganti.notion.site/Applied-LLMs-Mastery-2024-562ddaa27791463e9a1286199325045c) to the course website
##### [Feb 2024] Registrations are still open [click here](https://forms.gle/353sQMRvS951jDYu7) to register
🗓️\*Week 1 [Jan 15 2024]**\*: [Practical Introduction to LLMs](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week1_part1_foundations.md)**
- Applied LLM Foundations
- Real World LLM Use Cases
- Domain and Task Adaptation Methods
🗓️\*Week 2 [Jan 22 2024]**\*: [Prompting and Prompt
Engineering](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week2_prompting.md)**
- Basic Prompting Principles
- Types of Prompting
- Applications, Risks and Advanced Prompting
🗓️\*Week 3 [Jan 29 2024]**\*: [LLM Fine-tuning](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week3_finetuning_llms.md)**
- Basics of Fine-Tuning
- Types of Fine-Tuning
- Fine-Tuning Challenges
🗓️\*Week 4 [Feb 5 2024]**\*: [RAG (Retrieval-Augmented Generation)](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week4_RAG.md)**
- Understanding the concept of RAG in LLMs
- Key components of RAG
- Advanced RAG Methods
🗓️\*Week 5 [ Feb 12 2024]**\*: [Tools for building LLM Apps](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week5_tools_for_LLM_apps.md)**
- Fine-tuning Tools
- RAG Tools
- Tools for observability, prompting, serving, vector search etc.
🗓️\*Week 6 [Feb 19 2024]**\*: [Evaluation Techniques](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week6_llm_evaluation.md)**
- Types of Evaluation
- Common Evaluation Benchmarks
- Common Metrics
🗓️\*Week 7 [Feb 26 2024]**\*: [Building Your Own LLM Application](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week7_build_llm_app.md)**
- Components of LLM application
- Build your own LLM App end to end
🗓️\*Week 8 [March 4 2024]**\*: [Advanced Features and Deployment](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week8_advanced_features.md)**
- LLM lifecycle and LLMOps
- LLM Monitoring and Observability
- Deployment strategies
🗓️\*Week 9 [March 11 2024]**\*: [Challenges with LLMs](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week9_challenges_with_llms.md)**
- Scaling Challenges
- Behavioral Challenges
- Future directions
🗓️\*Week 10 [March 18 2024]**\*: [Emerging Research Trends](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week10_research_trends.md)**
- Smaller and more performant models
- Multimodal models
- LLM Alignment
🗓️*Week 11 *Bonus\* [March 25 2024]**\*: [Foundations](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/free_courses/Applied_LLMs_Mastery_2024/week11_foundations.md)**
- Generative Models Foundations
- Self-Attention and Transformers
- Neural Networks for Language
---
#### :book: List of Free GenAI Courses
##### LLM Basics and Foundations
1. [Large Language Models](https://rycolab.io/classes/llm-s23/) by ETH Zurich
2. [Understanding Large Language Models](https://www.cs.princeton.edu/courses/archive/fall22/cos597G/) by Princeton
3. [Transformers course](https://huggingface.co/learn/nlp-course/chapter1/1) by Huggingface
4. [NLP course](https://huggingface.co/learn/nlp-course/chapter1/1) by Huggingface
5. [CS324 - Large Language Models](https://stanford-cs324.github.io/winter2022/) by Stanford
6. [Generative AI with Large Language Models](https://www.coursera.org/learn/generative-ai-with-llms) by Coursera
7. [Introduction to Generative AI](https://www.coursera.org/learn/introduction-to-generative-ai) by Coursera
8. [Generative AI Fundamentals](https://www.cloudskillsboost.google/paths/118/course_templates/556) by Google Cloud
9. [5-Day Gen AI Intensive Course](https://www.youtube.com/watch?v=kpRyiJUUFxY&list=PLqFaTIg4myu-b1PlxitQdY0UYIbys-2es) by Google & Kaggle
10. [Introduction to Large Language Models](https://www.cloudskillsboost.google/paths/118/course_templates/539) by Google Cloud
11. [Introduction to Generative AI](https://www.cloudskillsboost.google/paths/118/course_templates/536) by Google Cloud
12. [Generative AI Concepts](https://www.datacamp.com/courses/generative-ai-concepts) by DataCamp (Daniel Tedesco Data Lead @ Google)
13. [1 Hour Introduction to LLM (Large Language Models)](https://www.youtube.com/watch?v=xu5_kka-suc) by WeCloudData
14. [LLM Foundation Models from the Ground Up | Primer](https://www.youtube.com/watch?v=W0c7jQezTDw&list=PLTPXxbhUt-YWjMCDahwdVye8HW69p5NYS) by Databricks
15. [Generative AI Explained](https://courses.nvidia.com/courses/course-v1:DLI+S-FX-07+V1/) by Nvidia
16. [Transformer Models and BERT Model](https://www.cloudskillsboost.google/course_templates/538) by Google Cloud
17. [Generative AI Learning Plan for Decision Makers](https://explore.skillbuilder.aws/learn/public/learning_plan/view/1909/generative-ai-learning-plan-for-decision-makers) by AWS
18. [Introduction to Responsible AI](https://www.cloudskillsboost.google/course_templates/554) by Google Cloud
19. [Fundamentals of Generative AI](https://learn.microsoft.com/en-us/training/modules/fundamentals-generative-ai/) by Microsoft Azure
20. [Generative AI for Beginners](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-122979-leestott) by Microsoft
21. [ChatGPT for Beginners: The Ultimate Use Cases for Everyone](https://www.udemy.com/course/chatgpt-for-beginners-the-ultimate-use-cases-for-everyone/) by Udemy
22. [[1hr Talk] Intro to Large Language Models](https://www.youtube.com/watch?v=zjkBMFhNj_g) by Andrej Karpathy
23. [ChatGPT for Everyone](https://learnprompting.org/courses/chatgpt-for-everyone) by Learn Prompting
24. [Large Language Models (LLMs) (In English)](https://www.youtube.com/playlist?list=PLxlkzujLkmQ9vMaqfvqyfvZV_o8EqjAk7) by Kshitiz Verma (JK Lakshmipat University, Jaipur, India)
25. [Generative AI for Beginners](https://codekidz.ai/lesson-intro/generative-a-362093) By CodeKidz, based on Microsoft's open sourced course.
##### Building LLM Applications
1. [LLMOps: Building Real-World Applications With Large Language Models](https://www.udacity.com/course/building-real-world-applications-with-large-language-models--cd13455) by Udacity
2. [Full Stack LLM Bootcamp](https://fullstackdeeplearning.com/llm-bootcamp/) by FSDL
3. [Generative AI for beginners](https://github.com/microsoft/generative-ai-for-beginners/tree/main) by Microsoft
4. [Large Language Models: Application through Production](https://www.edx.org/learn/computer-science/databricks-large-language-models-application-through-production) by Databricks
5. [Generative AI Foundations](https://www.youtube.com/watch?v=oYm66fHqHUM&list=PLhr1KZpdzukf-xb0lmiU3G89GJXaDbAIF) by AWS
6. [Introduction to Generative AI Community Course](https://www.youtube.com/watch?v=ajWheP8ZD70&list=PLmQAMKHKeLZ-iTT-E2kK9uePrJ1Xua9VL) by ineuron
7. [LLM University](https://docs.cohere.com/docs/llmu) by Cohere
8. [LLM Learning Lab](https://lightning.ai/pages/llm-learning-lab/) by Lightning AI
9. [LangChain for LLM Application Development](https://learn.deeplearning.ai/login?redirect_course=langchain&callbackUrl=https%3A%2F%2Flearn.deeplearning.ai%2Fcourses%2Flangchain) by Deeplearning.AI
10. [LLMOps](https://learn.deeplearning.ai/llmops) by DeepLearning.AI
11. [Automated Testing for LLMOps](https://learn.deeplearning.ai/automated-testing-llmops) by DeepLearning.AI
12. [Building Generative AI Applications Using Amazon Bedrock](https://explore.skillbuilder.aws/learn/course/external/view/elearning/17904/building-generative-ai-applications-using-amazon-bedrock-aws-digital-training) by AWS
13. [Efficiently Serving LLMs](https://learn.deeplearning.ai/courses/efficiently-serving-llms/lesson/1/introduction) by DeepLearning.AI
14. [Building Systems with the ChatGPT API](https://www.deeplearning.ai/short-courses/building-systems-with-chatgpt/) by DeepLearning.AI
15. [Serverless LLM apps with Amazon Bedrock](https://www.deeplearning.ai/short-courses/serverless-llm-apps-amazon-bedrock/) by DeepLearning.AI
16. [Building Applications with Vector Databases](https://www.deeplearning.ai/short-courses/building-applications-vector-databases/) by DeepLearning.AI
17. [Automated Testing for LLMOps](https://www.deeplearning.ai/short-courses/automated-testing-llmops/) by DeepLearning.AI
18. [Build LLM Apps with LangChain.js](https://www.deeplearning.ai/short-courses/build-llm-apps-with-langchain-js/) by DeepLearning.AI
19. [Advanced Retrieval for AI with Chroma](https://www.deeplearning.ai/short-courses/advanced-retrieval-for-ai/) by DeepLearning.AI
20. [Operationalizing LLMs on Azure](https://www.coursera.org/learn/llmops-azure) by Coursera
21. [Generative AI Full Course – Gemini Pro, OpenAI, Llama, Langchain, Pinecone, Vector Databases & More](https://www.youtube.com/watch?v=mEsleV16qdo) by freeCodeCamp.org
22. [Training & Fine-Tuning LLMs for Production](https://learn.activeloop.ai/courses/llms) by Activeloop
##### Prompt Engineering, RAG and Fine-Tuning
1. [LangChain & Vector Databases in Production](https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbVhnQW8xNDdhSU9IUDVLXzFhV2N0UkNRMkZrQXxBQ3Jtc0traUxHMzZJcGJQYjlyckYxaGxYVWlsOFNGUFlFVEdhNzdjTWpPUlQ2TF9XczRqNkxMVGpJTnd5YmYzV0prQ0IwZURNcHhIZ3h1Z051VTl5MXBBLUN0dkM0NHRkQTFua1Jpc0VCRFJUb0ZQZG95b0JqMA&q=https%3A%2F%2Flearn.activeloop.ai%2Fcourses%2Flangchain&v=gKUTDC13jys) by Activeloop
2. [Reinforcement Learning from Human Feedback](https://learn.deeplearning.ai/reinforcement-learning-from-human-feedback) by DeepLearning.AI
3. [Building Applications with Vector Databases](https://learn.deeplearning.ai/building-applications-vector-databases) by DeepLearning.AI
4. [Finetuning Large Language Models](https://learn.deeplearning.ai/finetuning-large-language-models) by Deeplearning.AI
5. [LangChain: Chat with Your Data](http://learn.deeplearning.ai/langchain-chat-with-your-data/) by Deeplearning.AI
6. [Building Systems with the ChatGPT API](https://learn.deeplearning.ai/chatgpt-building-system) by Deeplearning.AI
7. [Prompt Engineering with Llama 2](https://www.deeplearning.ai/short-courses/prompt-engineering-with-llama-2/) by Deeplearning.AI
8. [Building Applications with Vector Databases](https://learn.deeplearning.ai/building-applications-vector-databases) by Deeplearning.AI
9. [ChatGPT Prompt Engineering for Developers](https://learn.deeplearning.ai/chatgpt-prompt-eng/lesson/1/introduction) by Deeplearning.AI
10. [Advanced RAG Orchestration series](https://www.youtube.com/watch?v=CeDS1yvw9E4) by LlamaIndex
11. [Prompt Engineering Specialization](https://www.coursera.org/specializations/prompt-engineering) by Coursera
12. [Augment your LLM Using Retrieval Augmented Generation](https://courses.nvidia.com/courses/course-v1:NVIDIA+S-FX-16+v1/) by Nvidia
13. [Knowledge Graphs for RAG](https://www.deeplearning.ai/short-courses/knowledge-graphs-rag/) by Deeplearning.AI
14. [Open Source Models with Hugging Face](https://www.deeplearning.ai/short-courses/open-source-models-hugging-face/) by Deeplearning.AI
15. [Vector Databases: from Embeddings to Applications](https://www.deeplearning.ai/short-courses/vector-databases-embeddings-applications/) by Deeplearning.AI
16. [Understanding and Applying Text Embeddings](https://www.deeplearning.ai/short-courses/google-cloud-vertex-ai/) by Deeplearning.AI
17. [JavaScript RAG Web Apps with LlamaIndex](https://www.deeplearning.ai/short-courses/javascript-rag-web-apps-with-llamaindex/) by Deeplearning.AI
18. [Quantization Fundamentals with Hugging Face](https://www.deeplearning.ai/short-courses/quantization-fundamentals-with-hugging-face/) by Deeplearning.AI
19. [Preprocessing Unstructured Data for LLM Applications](https://www.deeplearning.ai/short-courses/preprocessing-unstructured-data-for-llm-applications/) by Deeplearning.AI
20. [Retrieval Augmented Generation for Production with LangChain & LlamaIndex](https://learn.activeloop.ai/courses/rag) by Activeloop
21. [Quantization in Depth](https://www.deeplearning.ai/short-courses/quantization-in-depth/) by Deeplearning.AI
##### Evaluation
1. [Building and Evaluating Advanced RAG Applications](https://learn.deeplearning.ai/building-evaluating-advanced-rag) by DeepLearning.AI
2. [Evaluating and Debugging Generative AI Models Using Weights and Biases](https://learn.deeplearning.ai/evaluating-debugging-generative-ai) by Deeplearning.AI
3. [Quality and Safety for LLM Applications](https://www.deeplearning.ai/short-courses/quality-safety-llm-applications/) by Deeplearning.AI
4. [Red Teaming LLM Applications](https://www.deeplearning.ai/short-courses/red-teaming-llm-applications/?utm_campaign=giskard-launch&utm_medium=headband&utm_source=dlai-homepage) by Deeplearning.AI
##### Multimodal
1. [How Diffusion Models Work](https://www.deeplearning.ai/short-courses/how-diffusion-models-work/) by DeepLearning.AI
2. [How to Use Midjourney, AI Art and ChatGPT to Create an Amazing Website](https://www.youtube.com/watch?v=5wdCev86RYE) by Brad Hussey
3. [Build AI Apps with ChatGPT, DALL-E and GPT-4](https://scrimba.com/learn/buildaiapps) by Scrimba
4. [11-777: Multimodal Machine Learning](https://www.youtube.com/playlist?list=PL-Fhd_vrvisNM7pbbevXKAbT_Xmub37fA) by Carnegie Mellon University
5. [Prompt Engineering for Vision Models](https://www.deeplearning.ai/short-courses/prompt-engineering-for-vision-models/) by Deeplearning.AI
##### Agents
1. [Building RAG Agents with LLMs](https://courses.nvidia.com/courses/course-v1:DLI+S-FX-15+V1/) by Nvidia
2. [Functions, Tools and Agents with LangChain](https://learn.deeplearning.ai/functions-tools-agents-langchain) by Deeplearning.AI
3. [AI Agents in LangGraph](https://www.deeplearning.ai/short-courses/ai-agents-in-langgraph/) by Deeplearning.AI
4. [AI Agentic Design Patterns with AutoGen](https://www.deeplearning.ai/short-courses/ai-agentic-design-patterns-with-autogen/) by Deeplearning.AI
5. [Multi AI Agent Systems with crewAI](https://www.deeplearning.ai/short-courses/multi-ai-agent-systems-with-crewai/) by Deeplearning.AI
6. [Building Agentic RAG with LlamaIndex](https://www.deeplearning.ai/short-courses/building-agentic-rag-with-llamaindex/) by Deeplearning.AI
7. [LLM Observability: Agents, Tools, and Chains](https://courses.arize.com/p/agents-tools-and-chains) by Arize AI
8. [Building Agentic RAG with LlamaIndex](https://www.deeplearning.ai/short-courses/building-agentic-rag-with-llamaindex/) by Deeplearning.AI
9. [Agents Tools & Function Calling with Amazon Bedrock (How-to)](https://www.youtube.com/watch?app=desktop&v=2L_XE6g3atI) by AWS Developers
10. [ChatGPT & Zapier: Agentic AI for Everyone](https://www.coursera.org/learn/agentic-ai-chatgpt-zapier) by Coursera
11. [Multi-Agent Systems with AutoGen](https://www.manning.com/books/multi-agent-systems-with-autogen) by Victor Dibia [Book]
12. [Large Language Model Agents MOOC, Fall 2024](https://llmagents-learning.org/f24) by Dawn Song & Xinyun Chen – A comprehensive course covering foundational and advanced topics on LLM agents.
13. [CS294/194-196 Large Language Model Agents](https://rdi.berkeley.edu/llm-agents/f24) by UC Berkeley
#### Miscellaneous
1. [Avoiding AI Harm](https://www.coursera.org/learn/avoiding-ai-harm) by Coursera
2. [Developing AI Policy](https://www.coursera.org/learn/developing-ai-policy) by Coursera
---
## :paperclip: Resources
- [ICLR 2024 Paper Summaries](https://areganti.notion.site/06f0d4fe46a94d62bff2ae001cfec22c?v=d501ca62e4b745768385d698f173ae14)
---
## :computer: Interview Prep
#### Topic wise Questions:
1. [Common GenAI Interview Questions](https://github.com/aishwaryanr/awesome-generative-ai-guide/blob/main/interview_prep/60_gen_ai_questions.md)
2. Prompting and Prompt Engineering
3. Model Fine-Tuning
4. Model Evaluation
5. MLOps for GenAI
6. Generative Models Foundations
7. Latest Research Trends
#### GenAI System Design (Coming Soon):
1. Designing an LLM-Powered Search Engine
2. Building a Customer Support Chatbot
3. Building a system for natural language interaction with your data.
4. Building an AI Co-pilot
5. Designing a Custom Chatbot for Q/A on Multimodal Data (Text, Images, Tables, CSV Files)
6. Building an Automated Product Description and Image Generation System for E-commerce
---
## :notebook: Code Notebooks
#### RAG Tutorials
- [AWS Bedrock Workshop Tutorials](https://github.com/aws-samples/amazon-bedrock-workshop) by Amazon Web Services
- [Langchain Tutorials](https://github.com/gkamradt/langchain-tutorials) by gkamradt
- [LLM Applications for production](https://github.com/ray-project/llm-applications/tree/main) by ray-project
- [LLM tutorials](https://github.com/ollama/ollama/tree/main/examples) by Ollama
- [LLM Hub](https://github.com/mallahyari/llm-hub) by mallahyari
- [RAG cookbook](https://docs.camel-ai.org/cookbooks/agents_with_rag.html) by CAMEL-AI
#### Fine-Tuning Tutorials
- [LLM Fine-tuning tutorials](https://github.com/ashishpatel26/LLM-Finetuning) by ashishpatel26
- [PEFT](https://github.com/huggingface/peft/tree/main/examples) example notebooks by Huggingface
- [Free LLM Fine-Tuning Notebooks](https://levelup.gitconnected.com/14-free-large-language-models-fine-tuning-notebooks-532055717cb7) by Youssef Hosni
#### Comprehensive LLM Code Repositories
- [LLM-PlayLab](https://github.com/Sakil786/LLM-PlayLab) This playlab encompasses a multitude of projects crafted through the utilization of Transformer Models
---
## :black_nib: Contributing
If you want to add to the repository or find any issues, please feel free to raise a PR and ensure correct placement within the relevant section or category.
---
## :pushpin: Cite Us
To cite this guide, use the below format:
```
@article{areganti_generative_ai_guide,
author = {Reganti, Aishwarya Naresh},
journal = {https://github.com/aishwaryanr/awesome-generative-ai-resources},
month = {01},
title = {{Generative AI Guide}},
year = {2024}
}
```
## License
[MIT License]
** This section is sponsored. We do not endorse or guarantee the product/service and are not responsible for any issues arising from its use. Please evaluate and use at your discretion.