Model Guide

• Model Guide
• Training NeMo Framework Models
  
  • Prepare Environment
    
    • Slurm
    • Base Command Platform
    • Kubernetes
    • General Configuration
  • Data Preparation
    
    • Data Preparation for GPT Models
      
      • Slurm
      • Base Command Platform
      • Kubernetes
      • Common
    • Data Preparation for T5 Models
      
      • Slurm
      • Base Command Platform
      • Common
    • Data Preparation for mT5 Models
      
      • Slurm
      • Base Command Platform
      • Common
    • Data Preparation for BERT Models
      
      • Slurm
      • Base Command Platform
      • Common
• Training with Predefined Configurations
  
  • Predefined Configurations of GPT Models
    
    • 126M configuration
    • 400M_improved configuration
    • 1B_improved configuration
    • 5B configuration
    • 7B_improved configuration
    • 20B configuration
    • 40B configuration
    • 40B_improved configuration
    • 175B configuration
    • FP8 with Transformer Engine
  • Predefined Configurations of T5 Models
    
    • 3B configuration
    • 11B configuration
    • 23B configuration
    • 41B configuration
  • Predefined Configurations of mT5 Models
    
    • 170M configuration
    • 390M configuration
    • 3B configuration
  • Training Logs with TensorBoard and Weights and Biases
  • Predefined Configurations of BERT Models
    
    • 110M configuration
    • 4B configuration
    • 20B configuration
    • 100B configuration
• Using AutoConfigurator to Find the Optimal Configuration
  
  • AutoConfigurator Capabilities
    
    • Model Size Recommendation
    • Base Configuration Generation
    • Training AutoConfigurator HP Search
    • Inference AutoConfigurator HP Search
  • Usage
    
    • General Configuration
      
      • Slurm
      • Base Command Platform
    • Predefined Configurations
      
      • Model Configuration
      • Base Configuration Generation
      • Training AutoConfigurator HP Search
      • Inference AutoConfigurator HP
    • Running Custom Model Size Configurations
    • Interpreting the Results
    • Logging Runs with Weights and Biases
• Training with Custom Configurations
  
  • Example: Changing Embedding Type for T5 Models
• Bring Your Own Dataset
  
  • Slurm
  • Base Command Platform
  • Kubernetes
  • Common
• Model Training
  
  • GPT Training
    
    • Slurm
    • Base Command Platform
    • Kubernetes
  • T5 Training
    
    • Slurm
    • Base Command Platform
  • mT5 Training
    
    • Slurm
    • Base Command Platform
  • BERT Training
    
    • Slurm
    • Base Command Platform
• Resuming Training with a Different Number of Nodes
• Checkpoint Conversion
  
  • GPT Conversion
    
    • Common
    • Slurm
    • Base Command Platform
    • Kubernetes
  • T5 Conversion
    
    • Common
    • Slurm
    • Base Command Platform
  • mT5 Conversion
    
    • Common
    • Slurm
    • Base Command Platform
• Generalized PEFT Framework
  
  • PEFT Training and Inference for GPT-style Models
  • PEFT Training and Inference
  • PEFT Training with NeMo Megatron Launcher
  • Common
  • Slurm
  • Base Command Platform
  • PEFT Training and Inference for mT5/T5-style Models
  • PEFT Training and Inference
• Model Fine-Tuning
  
  • T5 Fine-Tuning
    
    • Common
    • Slurm
    • Base Command Platform
  • mT5 Fine-Tuning
    
    • Common
    • Slurm
    • Base Command Platform
  • Fine-tuning on Custom Tasks
• Model Prompt Learning
  
  • GPT Prompt Learning
    
    • Common
    • Slurm
    • Base Command Platform
  • T5 and mT5 Prompt Learning
    
    • Common
    • Slurm
    • Base Command Platform
• Model Adapter Learning and IA3 Learning
  
  • GPT Adapter Learning and IA3 Learning
    
    • Common
    • Slurm
    • Base Command Platform
  • T5 Adapter Learning and IA3 Learning
    
    • Common
    • Slurm
    • Base Command Platform
• Model Evaluation
  
  • GPT Evaluation
    
    • Common
    • Slurm
    • Base Command Platform
    • Kubernetes
  • T5 Evaluation
    
    • Common
    • Slurm
    • Base Command Platform
  • mT5 Evaluation
    
    • Common
    • Slurm
    • Base Command Platform
  • Prompt-Learned GPT Evaluation
    
    • Common
    • Slurm
    • Base Command Platform
  • Prompt-Learned T5 and mT5 Evaluation
    
    • Common
    • Slurm
    • Base Command Platform
  • Adapter-Learned and IA3-Learned GPT Evaluation
    
    • Common
    • Slurm
    • Base Command Platform
  • Adapter-Learned and IA3-Learned T5 Evaluation
    
    • Common
    • Slurm
    • Base Command Platform
• Exporting the NeMo Models to TensorRT-LLM
  
  • Supported Model and GPUs
  • User Guide
  • NeMo Export Module and APIs
    
    • PyTest for Export Module
• NeMo Data Curator
  
  • Coverage
  • General Usage
  • Module-specific documentation
    
    • NeMo Data Curator
    • Downloading and extracting text
      
      • Preparing documents from Common Crawl
    • Document filtering
    • Text cleaning and language separation
    • Exact and fuzzy deduplication
      
      • Exact deduplication
      • Fuzzy deduplication
    • Classifier and heuristic-based quality filtering
      
      • Classifier filtering
      • Heuristic filtering
    • 1 Downstream task decontamination (task deduplication)
    • prepare_task_data
    • 3 Find the matching task N-grams within the training documents
    • 4 Remove matching N-grams above a user-defined threshold.