A Hackers' Guide to Language Models

Step-by-Step Tutorial:

1. Understanding Language Models:

• Watch the video titled "A Hackers' Guide to Language Models" by Jeremy Howard on the channel "Jeremy Howard" for an in-depth understanding of language models.

2. Pre-requisite Knowledge:

• Familiarize yourself with the basics of deep learning before proceeding to understand language models effectively.
• Consider taking the free course at course.fast.ai and watch the first five lessons to grasp the fundamental concepts of deep learning.

3. Exploring Language Models:

• Learn about language models that predict the next word in a sentence or fill in missing words.
• Explore examples of open AI language models like Text DaVinci 003 to understand how they predict the next words in a sentence.

4. Tokenization and Decoding:

• Understand tokenization, where words are converted into numerical tokens for processing.
• Decode the tokens using the tokenizer to understand the predicted words by the language model.

5. ULM Fit Approach:

• Learn about the ULM Fit approach developed by Jeremy Howard and Sebastian Rooter in 2017 for training language models on Wikipedia data.

6. Language Model Fine-Tuning:

• Explore the concept of fine-tuning language models to adapt them for specific tasks or questions.
• Understand the importance of using datasets like OpenAI's OpenAlkER for fine-tuning language models effectively.

7. Advanced Data Analysis:

• Explore advanced data analysis techniques using language models to perform tasks like code generation, text extraction from images, and more.

8. Running Language Models:

• Choose between using open AI's API or running language models on your own GPU for specific tasks.
• Consider options like Hugging Face's Transformers library for accessing pre-trained models or creating your own fine-tuned models.

9. Retrieval Augmented Generation:

• Implement retrieval augmented generation to enhance language model responses by providing contextual documents for better answers.

10. Fine-Tuning Models:

• Fine-tune language models using tools like Axolotl or llama.cpp to customize models for specific tasks or questions effectively.

11. Exploring Other Options:

• Explore options like mlc and llama.cpp for running language models on various platforms including mobile devices and web browsers.

12. Joining the Community:

• Join communities like the First AI Discord channel or other forums to connect with experts and enthusiasts for guidance and support in working with language models.

By following these steps, you can gain a comprehensive understanding of language models and leverage them effectively for various tasks and applications.