Mastering Generative AI and LLM Deployment.

About this course

This course is diving into Generative AI State-Of-Art Scientific Challenges. It helps to uncover ongoing problems and develop or customize your Own Large Models Applications. Course mainly is suitable for any candidates(students, engineers,experts) that have great motivation to Large Language Models with Todays-Ongoing Challenges as well as their deeployment with Python Based and Javascript Web Applications, as well as with Python Programming Languagess. Candidates will have practical lab exercies based on Small LLM training, Quaantization and Deployment stages. Candidates will develop all END-END LLM Applications, starting from training till Deployment Quaantization Fase. In addition, one will be able to optimize and quantize TensorRT frameworks for deployment in variety of sectors. Moreover, They will learn deployment of LLM quantized model to Web Pages developed with React, Javascript and FLASKHere you will also learn how to integrate Reinforcement Learning(PPO) to Large Language Model, in order to fine them with Human Feedback based. Candidates will learn how to code and debug in C/C++ Programming languages at least in intermediate level.

LLM Models used: The Falcon, LLAMA2, BLOOM, MPT, Vicuna,FLAN-T5, GPT2/GPT3, GPT NEOXBERT 101, Distil BERTFINE-Tuning Small Models under supervision of BIG ModelsImage Generation :LLAMA models

Gemini Dall-E OpenAIHugging face ModelsQuantization Techniques and Principles:1. Lora and Qlora2. TensorRT principles3. All Possible Quantizization Techniques.

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