Completed
Uploading FLUX LoRAs to Hugging Face for Easy Access and Sharing
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Blazing Fast and Ultra Cheap FLUX LoRA Training on Cloud Compute - No GPU Required
Automatically move to the next video in the Classroom when playback concludes
- 1 Introduction to FLUX Training on Cloud Services Massed Compute and RunPod
- 2 Overview of Platform Differences and Why Massed Compute is Preferred for FLUX Training
- 3 Quick Setup for Massed Compute and RunPod Accounts
- 4 Overview of FLUX, Kohya GUI, and Using 4x GPUs for Fast Training
- 5 Exploring Massed Compute Coupons and Discounts: How to Save on GPU Costs
- 6 Detailed Setup for Training FLUX on Massed Compute: Account Creation, Billing, and Deploying Instances
- 7 Deploying Multiple GPUs on Massed Compute for Faster Training
- 8 Setting Up ThinLinc Client for File Transfers Between Local Machine and Cloud
- 9 Troubleshooting ThinLinc File Transfer Issues on Massed Compute
- 10 Preparing to Install Kohya GUI and Download Necessary Models on Massed Compute
- 11 Upgrading to the Latest Version of Kohya for FLUX Training
- 12 Downloading FLUX Training Models and Preparing the Dataset
- 13 Checking VRAM Usage with nvitop: Real-Time Monitoring During FLUX Training
- 14 Speed Optimization Tips: Disabling T5 Attention Mask for Faster Training
- 15 Understanding the Trade-offs: Applying T5 Attention Mask vs. Training Speed
- 16 Setting Up Multi-GPU Training for FLUX on Massed Compute
- 17 Adjusting Epochs and Learning Rate for Multi-GPU Training
- 18 Achieving Near-Linear Speed Gain with 4x GPUs on Massed Compute
- 19 Uploading FLUX LoRAs to Hugging Face for Easy Access and Sharing
- 20 Using SwarmUI on Your Local Machine via Cloudflare for Image Generation
- 21 Moving Models to the Correct Folders in SwarmUI for FLUX Image Generation
- 22 Setting Up and Running Grid Generation to Compare Different Checkpoints
- 23 Downloading and Managing LoRAs and Models on Hugging Face
- 24 Generating Images with FLUX on SwarmUI and Finding the Best Checkpoints
- 25 Advanced Configurations in SwarmUI for Optimized Image Generation
- 26 How to Use Forge Web UI with FLUX Models on Massed Compute
- 27 Setting Up and Configuring Forge Web UI for FLUX on Massed Compute
- 28 Moving Models and LoRAs to Forge Web UI for Image Generation
- 29 Generating Images with LoRAs on Forge Web UI
- 30 Transition to RunPod: Setting Up FLUX Training and Using SwarmUI/Forge Web UI
- 31 RunPod Network Volume Storage: Setup and Integration with FLUX Training
- 32 Differences Between Massed Compute and RunPod: Speed, Cost, and Hardware
- 33 Deploying Instances on RunPod and Setting Up JupyterLab
- 34 Installing Kohya GUI and Downloading Models for FLUX Training on RunPod
- 35 Preparing Datasets and Starting FLUX Training on RunPod
- 36 Monitoring VRAM and Training Speed on RunPod’s A40 GPUs
- 37 Optimizing Training Speed by Disabling T5 Attention Mask on RunPod
- 38 Comparing GPU Performance Across Platforms: A6000 vs A40 in FLUX Training
- 39 Setting Up Multi-GPU Training on RunPod for Faster FLUX Training
- 40 Adjusting Learning Rate and Epochs for Multi-GPU Training on RunPod
- 41 Achieving Near-Linear Speed Gain with Multi-GPU FLUX Training on RunPod
- 42 Completing FLUX Training on RunPod and Preparing Models for Use
- 43 Managing Multiple Checkpoints: Best Practices for FLUX Training
- 44 Using SwarmUI on RunPod for Image Generation with FLUX LoRAs
- 45 Setting Up Multiple Backends on SwarmUI for Multi-GPU Image Generation
- 46 Generating Images and Comparing Checkpoints on SwarmUI on RunPod
- 47 Uploading FLUX LoRAs to Hugging Face from RunPod for Easy Access
- 48 Advanced Download Techniques: Using Hugging Face CLI for Batch Downloads
- 49 Fast Download and Upload of Models and LoRAs on Hugging Face
- 50 Using Forge Web UI on RunPod for Image Generation with FLUX LoRAs
- 51 Troubleshooting Installation Issues with Forge Web UI on RunPod
- 52 Generating Images on Forge Web UI with FLUX Models and LoRAs
- 53 Conclusion and Upcoming Research on Fine-Tuning FLUX with CLIP Large Models
