Linkedin - LLaMa for Developers
- CategoryOther
- TypeTutorials
- LanguageEnglish
- Total size257.7 MB
- Uploaded Byfreecoursewb
- Downloads103
- Last checkedApr. 28th '24
- Date uploadedApr. 27th '24
- Seeders 9
- Leechers8
LLaMa for Developers
https://FreeCourseWeb.com
Released 4/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 35m | Size: 258 MB
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:
[ FreeCourseWeb.com ] Linkedin - LLaMa for Developers- Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 01 - Introduction
- 01 - Developing AI models using LLaMA.mp4 (3.2 MB)
- 01 - Developing AI models using LLaMA.srt (1.0 KB)
- 01 - Using LLaMA online.mp4 (2.4 MB)
- 01 - Using LLaMA online.srt (1.9 KB)
- 02 - Running LLaMA in a notebook.mp4 (18.6 MB)
- 02 - Running LLaMA in a notebook.srt (9.0 KB)
- 03 - Accessing LLaMA in an enterprise environment.mp4 (5.1 MB)
- 03 - Accessing LLaMA in an enterprise environment.srt (2.8 KB)
- 01 - The LLaMA architecture.mp4 (5.0 MB)
- 01 - The LLaMA architecture.srt (5.0 KB)
- 02 - The LLaMA tokenizer.mp4 (5.2 MB)
- 02 - The LLaMA tokenizer.srt (6.3 KB)
- 03 - The LLaMA context window.mp4 (3.7 MB)
- 03 - The LLaMA context window.srt (4.4 KB)
- 04 - Differences between LLaMA 1 and 2.mp4 (4.0 MB)
- 04 - Differences between LLaMA 1 and 2.srt (4.1 KB)
- 01 - Fine-tuning LLaMA with a few examples.mp4 (12.0 MB)
- 01 - Fine-tuning LLaMA with a few examples.srt (8.1 KB)
- 02 - Fine-tuning LLaMA and freezing layers.mp4 (19.1 MB)
- 02 - Fine-tuning LLaMA and freezing layers.srt (11.9 KB)
- 03 - Fine-tuning with LLaMA using LoRa.mp4 (18.0 MB)
- 03 - Fine-tuning with LLaMA using LoRa.srt (10.6 KB)
- 04 - Reinforcement learning with RLHF and DPO.mp4 (16.2 MB)
- 04 - Reinforcement learning with RLHF and DPO.srt (9.8 KB)
- 05 - Fine-tuning larger LLaMA models.mp4 (7.2 MB)
- 05 - Fine-tuning larger LLaMA models.srt (4.4 KB)
- 01 - Resources required to serve LLaMA.mp4 (6.9 MB)
- 01 - Resources required to serve LLaMA.srt (7.8 KB)
- 02 - Quantizing LLaMA.mp4 (12.0 MB)
- 02 - Quantizing LLaMA.srt (7.1 KB)
- 03 - Using TGI for serving LLaMA.mp4 (6.7 MB)
- 03 - Using TGI for serving LLaMA.srt (4.7 KB)
- 04 - Using VLLM for serving LLaMA.mp4 (19.8 MB)
- 04 - Using VLLM for serving LLaMA.srt (9.4 KB)
- 05 - Using DeepSpeed for serving LLaMA.mp4 (16.2 MB)
- 06 - Explaining LoRA and SLoRA.mp4 (4.9 MB)
- 06 - Explaining LoRA and SLoRA.srt (3.6 KB)
- 07 - Using a vendor for serving LLaMA.mp4 (7.3 MB)
- 07 - Using a vendor for serving LLaMA.srt (4.8 KB)
- 01 - Difference between LLaMA with commercial LLMs.mp4 (11.0 MB)
- 01 - Difference between LLaMA with commercial LLMs.srt (7.0 KB)
- 02 - Few shot learning with LLaMA.mp4 (15.0 MB)
- 02 - Few shot learning with LLaMA.srt (9.1 KB)
- 03 - Chain of thought with LLaMA.mp4 (8.8 MB)
- 03 - Chain of thought with LLaMA.srt (6.0 KB)
- 04 - Using schemas with LLaMA.mp4 (8.4 MB)
- 04 - Using schemas with LLaMA.srt (4.7 KB)
- 05 - Optimizing LLaMA prompts with DSPy.mp4 (15.6 MB)
- 05 - Optimizing LLaMA prompts with DSPy.srt (8.4 KB)
- 06 - Challenge Generating product tags.mp4 (683.3 KB)
- 06 - Challenge Generating product tags.srt (0.7 KB)
- 07 - Solution Generating product tags.mp4 (3.0 MB)
- 07 - Solution Generating product tags.srt (1.7 KB)
- 01 - Continue your LlaMA AI model development journey.mp4 (1.6 MB)
- 01 - Continue your LlaMA AI model development journey.srt (0.8 KB)
- Bonus Resources.txt (0.4 KB)
Code:
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