Linkedin - LLaMa for Developers

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size364.9 MB
  • Uploaded ByxHOBBiTx
  • Downloads121
  • Last checkedMay. 16th '24
  • Date uploadedMay. 15th '24
  • Seeders 16
  • Leechers3
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Infohash : C5B810A8A51FCF93FAC544CE014A8AD60ACBB6BF

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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.

Files:

Linkedin - LLaMa for Developers 1. Introduction
  • 1. Developing AI models using LLaMA.mp4 (5.6 MB)
2. Introduction to LLaMA
  • 1. Using LLaMA online.mp4 (3.1 MB)
  • 2. Running LLaMA in a notebook.mp4 (28.5 MB)
  • 3. Accessing LLaMA in an enterprise environment.mp4 (7.2 MB)
3. LLaMA Architecture
  • 1. The LLaMA architecture.mp4 (5.9 MB)
  • 2. The LLaMA tokenizer.mp4 (5.9 MB)
  • 3. The LLaMA context window.mp4 (4.2 MB)
  • 4. Differences between LLaMA 1 and 2.mp4 (4.8 MB)
4. Fine-Tuning LLaMA
  • 1. Fine-tuning LLaMA with a few examples.mp4 (17.6 MB)
  • 2. Fine-tuning LLaMA and freezing layers.mp4 (27.6 MB)
  • 3. Fine-tuning with LLaMA using LoRa.mp4 (26.6 MB)
  • 4. Reinforcement learning with RLHF and DPO.mp4 (22.7 MB)
  • 5. Fine-tuning larger LLaMA models.mp4 (10.0 MB)
5. Serving LLaMA
  • 1. Resources required to serve LLaMA.mp4 (7.9 MB)
  • 2. Quantizing LLaMA.mp4 (17.5 MB)
  • 3. Using TGI for serving LLaMA.mp4 (9.4 MB)
  • 4. Using VLLM for serving LLaMA.mp4 (28.4 MB)
  • 5. Using DeepSpeed for serving LLaMA.mp4 (24.3 MB)
  • 6. Explaining LoRA and SLoRA.mp4 (6.7 MB)
  • 7. Using a vendor for serving LLaMA.mp4 (9.6 MB)
6. Prompting LLaMA
  • 1. Difference between LLaMA with commercial LLMs.mp4 (15.6 MB)
  • 2. Few shot learning with LLaMA.mp4 (20.8 MB)
  • 3. Chain of thought with LLaMA.mp4 (12.4 MB)
  • 4. Using schemas with LLaMA.mp4 (11.8 MB)
  • 5. Optimizing LLaMA prompts with DSPy.mp4 (23.3 MB)
  • 6. Challenge- Generating product tags.mp4 (794.1 KB)
  • 7. Solution- Generating product tags.mp4 (4.4 MB)
7. Conclusion
  • 1. Continue your LlaMA AI model development journey.mp4 (2.3 MB)

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