LLMs Workshop: Practical Exercises of Large Language Models
Category: Tutorials
- views: 361
- date: 10 April 2024
- posted by: AD-TEAM
LLMs Workshop: Practical Exercises of Large Language Models
Published 4/2024
Duration: 3h57m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 1.79 GB
Genre: eLearning | Language: English [/center]
Practice Large Language Models with Amazing Exercises
What you'll learn
Deep Learning
Transformers
Langchain
Large Language Models
Requirements
Python Knowledge
Basic Deep Learning Knowledge
Transformers knowledge is desirable
Description
Dive into the revolutionary world of Large Language Models (LLMs) with our comprehensive 4-hour workshop, designed to bridge the gap between theoretical knowledge and practical skills. Whether you're a budding data scientist, an AI enthusiast, or a seasoned professional looking to expand your toolkit, this course is tailored to empower you with hands-on experience in leveraging LLMs for a variety of real-world applications.
What You'll Learn:
Fundamentals and Advanced Techniques:
Start with the basics of Large Language Models, including their architecture and capabilities, before progressing to advanced optimization methods such as Quantization and LoRA.
Practical Exercises:
Engage in structured exercises using Kaggle datasets in Colab, fine-tuning models for tasks like question answering and text summarization with QLoRA, and exploring cutting-edge concepts such as Retrieval Augmented Generation (RAG).
Real-World Applications:
Tackle engaging projects like building a semantic search engine to find movies and developing a chat interface with scholarly articles, applying your knowledge in tangible, impactful ways.
Model Publication:
As a bonus, learn how to share your fine-tuned models with the world through Huggingface, enhancing your visibility in the AI community.
Intended Learners:
This course is perfect for individuals looking to deepen their understanding of LLMs and apply these models in innovative ways. Ideal for AI professionals, data scientists, and researchers eager to expand their skills and apply LLMs to solve complex problems.
Who this course is for:
Deep learning Engineers
Deep Learning enthusiasts
Machine Learning Engineers
Artificial intelligence Engineers
More Info
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