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Course details In this course, learn how to customize open-source AI models with one of the most common open-source models, LLaMa (Large Language Model Meta AI). Instructor Denys Linkov shares a hands-on approach to working with LLaMa, explaining LLaMa architecture, prompting, deploying, and training models. He uses a series of Python notebooks to show you how to adapt LLaMa to your use cases and employ it in an enterprise or startup environment

1. 1. Introduction/1. Developing AI models using LLaMA.mp45.61 MiB
2. 2. Introduction to LLaMA/1. Using LLaMA online.mp43.09 MiB
3. 2. Introduction to LLaMA/2. Running LLaMA in a notebook.mp428.46 MiB
4. 2. Introduction to LLaMA/3. Accessing LLaMA in an enterprise environment.mp47.19 MiB
5. 3. LLaMA Architecture/1. The LLaMA architecture.mp45.91 MiB
6. 3. LLaMA Architecture/2. The LLaMA tokenizer.mp45.9 MiB
7. 3. LLaMA Architecture/3. The LLaMA context window.mp44.17 MiB
8. 3. LLaMA Architecture/4. Differences between LLaMA 1 and 2.mp44.81 MiB
9. 4. Fine-Tuning LLaMA/1. Fine-tuning LLaMA with a few examples.mp417.62 MiB
10. 4. Fine-Tuning LLaMA/2. Fine-tuning LLaMA and freezing layers.mp427.64 MiB
11. 4. Fine-Tuning LLaMA/3. Fine-tuning with LLaMA using LoRa.mp426.63 MiB
12. 4. Fine-Tuning LLaMA/4. Reinforcement learning with RLHF and DPO.mp422.71 MiB
13. 4. Fine-Tuning LLaMA/5. Fine-tuning larger LLaMA models.mp410.04 MiB
14. 5. Serving LLaMA/1. Resources required to serve LLaMA.mp47.9 MiB
15. 5. Serving LLaMA/2. Quantizing LLaMA.mp417.5 MiB
16. 5. Serving LLaMA/3. Using TGI for serving LLaMA.mp49.38 MiB
17. 5. Serving LLaMA/4. Using VLLM for serving LLaMA.mp428.37 MiB
18. 5. Serving LLaMA/5. Using DeepSpeed for serving LLaMA.mp424.28 MiB
19. 5. Serving LLaMA/6. Explaining LoRA and SLoRA.mp46.73 MiB
20. 5. Serving LLaMA/7. Using a vendor for serving LLaMA.mp49.56 MiB
21. 6. Prompting LLaMA/1. Difference between LLaMA with commercial LLMs.mp415.58 MiB
22. 6. Prompting LLaMA/2. Few shot learning with LLaMA.mp420.75 MiB
23. 6. Prompting LLaMA/3. Chain of thought with LLaMA.mp412.41 MiB
24. 6. Prompting LLaMA/4. Using schemas with LLaMA.mp411.78 MiB
25. 6. Prompting LLaMA/5. Optimizing LLaMA prompts with DSPy.mp423.33 MiB
26. 6. Prompting LLaMA/6. Challenge- Generating product tags.mp4794.05 KiB
27. 6. Prompting LLaMA/7. Solution- Generating product tags.mp44.41 MiB
28. 7. Conclusion/1. Continue your LlaMA AI model development journey.mp42.31 MiB