Description
Deploying Open-source LLMs. This course covers the practical deployment of large open-source language models from selection to maintenance in a production environment. You will learn the complete process of selecting the right model based on criteria such as performance, cost, and security considerations. The training includes configuring development and production environments, optimizing models with techniques such as quantization to improve speed and reduce resource consumption, and deploying them using specialized frameworks. A major part is also dedicated to securing deployments, which includes protecting data pipelines, securing access points, and implementing monitoring mechanisms. Finally, methods for managing, monitoring performance, and updating these models in real-world scenarios are taught to achieve an optimal balance between reliability, performance, and security in end systems.
What you will learn
- Choosing the right strategy: How to match deployment methods to organizational needs such as latency, privacy, and budget.
- Configuring the technical environment: Setting up service frameworks and preparing the necessary infrastructure for AI models.
- Hardware optimization: Understanding hardware requirements and selecting appropriate graphics processing units (GPUs) for optimal model execution.
- Quantization Techniques: Learn Model Quantization methods to reduce model size without significant loss of quality.
- Production environment management: implementing governance processes, performance monitoring, and rollback systems.
- Security and accessibility: Methods for securing endpoints and protecting sensitive data when using open source models.
- Reduce infrastructure costs: Use intelligent solutions to manage cloud and on-premises computing costs.
This course is suitable for people who:
- Machine Learning Engineers: People who aim to move AI models from research to operational environments.
- Data Scientists: Those who seek complete control over language models and their personalization.
- Cloud solution architects: professionals responsible for designing and managing the infrastructure required for AI workloads.
- Software developers: Programmers who want to integrate the capabilities of large open source language models into their applications.
- Technical and IT managers: People looking to reduce their dependence on paid AI services and use open source and secure solutions.
- DevSecOps professionals: Those who oversee the security and stability of large-scale deployments.
Deploying Open-source LLMs Course Details
- Publisher: Pluralsight
- Instructor: Navidut Tauhid
- Education level: Intermediate
- Training duration: 1 hour and 16 minutes
Course headings
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
248 MB
