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Course Outline
Introduction to DeepSeek LLM Fine-Tuning
- Overview of DeepSeek models, such as DeepSeek-R1 and DeepSeek-V3
- Understanding the necessity for fine-tuning large language models (LLMs)
- Comparison between fine-tuning and prompt engineering
Preparing the Dataset for Fine-Tuning
- Curating datasets specific to the domain of interest
- Techniques for data preprocessing and cleaning
- Tokenization and dataset formatting for DeepSeek LLMs
Setting Up the Fine-Tuning Environment
- Configuring GPU and TPU acceleration for enhanced performance
- Setting up Hugging Face Transformers with DeepSeek LLMs for government use
- Understanding hyperparameters critical for fine-tuning processes
Fine-Tuning DeepSeek LLM
- Implementing supervised fine-tuning techniques
- Utilizing Low-Rank Adaptation (LoRA) and Parameter-Efficient Fine-Tuning (PEFT)
- Executing distributed fine-tuning for large-scale datasets
Evaluating and Optimizing Fine-Tuned Models
- Assessing model performance using evaluation metrics
- Addressing issues of overfitting and underfitting
- Enhancing inference speed and model efficiency
Deploying Fine-Tuned DeepSeek Models
- Packaging models for API deployment in government applications
- Integrating fine-tuned models into existing systems and applications
- Scaling deployments using cloud and edge computing resources
Real-World Use Cases and Applications
- Application of fine-tuned LLMs in finance, healthcare, and customer support for government services
- Case studies highlighting industry applications and best practices
- Ethical considerations in the deployment of domain-specific AI models
Summary and Next Steps
Requirements
- Experience with machine learning and deep learning frameworks for government applications
- Familiarity with transformers and large language models (LLMs)
- Understanding of data preprocessing and model training techniques
Audience
- AI researchers exploring LLM fine-tuning for government projects
- Machine learning engineers developing custom AI models for government use
- Advanced developers implementing AI-driven solutions for government initiatives
21 Hours
