Clean and Curate Data for AI Fine-Tuning
Establish guidelines for obtaining RAW Data
Go from Drowning in Data to Clean Data
Fine-Tune AI Models with PyTorch
Understand AI architecture: Transformer model
Describe tokenization and word embeddings
Install and use AI frameworks like Llama-3
Perform LoRA and QLoRA Fine-Tuning
Explore model quantization and fine-tuning
Deploy and Maximize AI Model Performance
Essential Skills Gained
Clean and Curate Data for AI Fine-Tuning
Establish guidelines for obtaining RAW Data
Go from Drowning in Data to Clean Data
Fine-Tune AI Models with PyTorch
Format
3 day course with lecture and hands-on labs.
Audience
Project Managers
Architects
Developers
Data Acquisition Specialists
Description
You will develop the skills to gather, clean, and organize data for fine-tuning pre-trained LLMs and Generative AI models. Through a combination of lectures and hands-on labs, you will use Python to fine-tune open-source Transformer models. Gain practical experience with LLM frameworks, learn essential training techniques, and explore advanced topics such as quantization. During the hands-on labs, you will access a GPU-accelerated server for practical experience with industry-standard tools and frameworks.
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Let us tailor the course to your needs at no extra cost.