Playbooks

• Playbooks
• Running NeMo Framework on DGX Cloud
  
  • Pre-Requisites
  • Steps
    
    • Setup
      
      • Pushing the container
      • Creating a workspace
      • Mounting the workspace locally
    • Data Preparation
    • Model Training
  • Next Steps
• Running NeMo Framework on Kubernetes
  
  • Pre-Requisites
  • Steps
    
    • Setup
    • Data Preparation
    • Model Training
  • Next Steps
  • Troubleshooting
• Foundation Model Pre-training using NeMo Framework
  
  • Project Description
    
    • Learning Goals
    • NeMo Tools and Resources
    • Data
    • Requirements
      
      • Software
      • Hardware
  • Project Instructions and Milestones
  • Project Deliverables
  • Project Evaluation
• NeMo Framework AutoConfigurator
  
  • Project Description
    
    • Learning Goals
    • NeMo Tools and Resources
    • Data
    • Requirements
      
      • Playbook - NeMo Framework Model Pre-training
      • Software
      • Hardware
  • Project Instructions and Milestones
  • [1] Model Size Recommendation
  • [2] Getting the optimal hyperparameters for training and inference for a given model size and compute budget
  • Project Deliverables
  • Project Evaluation
• NeMo Framework Supervised fine-tuning (SFT) with Llama2
  
  • Project Description
    
    • Learning Goals
    • NeMo Tools and Resources
    • Software Requirements
    • Hardware Requirements
    • Data
  • [Optional] Convert Llama2 from Huggingface format to NeMo format
    
    • Optional Step 1: Download llama2 in huggingface format
    • Optional Step 2: Convert to .nemo
  • Prepare data
    
    • Step 1: Download dataset
    • Step 2: Data Preprocessing
    • Step 3: Split the data into train, validation and test.
  • Step 4: Run the SFT finetuning script
    
    • Step 6: Run evaluation
• NeMo Framework PEFT with Llama2
  
  • Project Description
    
    • Learning Goals
    • NeMo Tools and Resources
    • Educational Resources
    • Software Requirements
    • Hardware Requirements
  • [Optional] Convert Llama2 from Huggingface format to NeMo format
    
    • Step 1: Download llama2 in huggingface format
    • Step 2: Convert to .nemo
  • Prepare data
    
    • Step 1: Download the PubMedQA dataset and run the split_dataset.py script in the cloned directory.
    • Step 2: Data Preprocessing
  • Run the PEFT finetuning script
    
    • Step 1: Set the experiment configs
    • Step 2: Run PEFT training
    • Step 3: Run inference