ParlAI for Conversational AI Training Course
ParlAI is an open-source, Python-based platform that assists users in training, configuring, and evaluating dialogue models for conversational AI applications. It seamlessly integrates with existing chat services and offers a variety of datasets and reference models to enhance dialog AI research.
This instructor-led live training, available either online or onsite, is designed for researchers and developers who want to install, configure, customize, and manage the ParlAI platform to develop their own AI models.
Upon completion of this training, participants will be equipped to share, train, and evaluate AI models, enabling them to build and develop conversational solutions across existing chat services.
Course Format
- Interactive lectures and discussions.
- Numerous exercises and practice sessions.
- Hands-on implementation within a live lab environment.
Course Customization Options
- For a customized training session, please contact us to make arrangements.
Course Outline
Introduction
Overview of ParlAI Features and Architecture
- ParlAI framework
- Key capabilities and goals
- Core concepts (agents, messages, teachers, and worlds)
Getting Started with ParlAI for Conversational AI
- Installation
- Adding a simple model
- Simple display data script
- Validation and testing
- Tasks
- Agent training and evaluation
- Interacting with models
Working with Tasks and Datasets in ParlAI
- Adding datasets
- Separating data into sets (train, valid, or test)
- Using JSON instead of a text file
- Creating and executing tasks
Exploring Worlds, Sharing, and Batching
- The concept of Worlds
- Agent sharing
- Implementing batching
- Dynamic batching
Using Torch Generator and Ranker Agents
- Torch generator agent
- Torch ranker agent
- Example models
- Creating models
- Training and evaluating models
Adding Built-In and Custom Metrics
- Standard metrics
- Adding custom metrics
- Teacher metrics
- Agent level metrics (global and local)
- List of metrics
Speeding up Training Runs in ParlAI
- Setting a baseline
- Skip generation command
- Dynamic batching training command
- Using FP16 and multiple GPUs
- Background preprocessing
Exploring Other ParlAI Topics
- Using and writing mutators
- Running crowdsourcing tasks
- Using existing chat services
- Swapping out transformer subcomponents
- Running and writing tests
- ParlAI tips and tricks
Troubleshooting
Summary and Conclusion
Requirements
- Proficiency in Python or other programming languages.
- A general understanding of artificial intelligence (AI) concepts.
Audience
- Researchers
- Developers
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793
ParlAI for Conversational AI Training Course - Enquiry
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