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The below text quoted from resource : https://huggingface.co/ostris/OpenFLUX.1

Beta Version v0.1.0

After numerous iterations and spending way too much of my own money on compute to train this, I think it is finally at the point I am happy to consider it a beta. I am still going to continue to train it, but the distillation has been mostly trained out of it at this point. So phase 1 is complete. Feel free to use it and fine tune it, but be aware that I will likely continue to update it.

What is this?

This is a fine tune of the FLUX.1-schnell model that has had the distillation trained out of it. Flux Schnell is licensed Apache 2.0, but it is a distilled model, meaning you cannot fine-tune it. However, it is an amazing model that can generate amazing images in 1-4 steps. This is an attempt to remove the distillation to create an open source, permissivle licensed model that can be fine tuned.

How to Use

Since the distillation has been fine tuned out of the model, it uses classic CFG. Since it requires CFG, it will require a different pipeline than the original FLUX.1 schnell and dev models. This pipeline can be found in open_flux_pipeline.py in this repo. I will be adding example code in the next few days, but for now, a cfg of 3.5 seems to work well.

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Performance

• Improved launch speed for large datasets (>1M samples)
• Improved speed for quantising on CPU
• Optional support for directly quantising on GPU near-instantly (--quantize_via)

Compatibility

• SDXL, SD1.5 and SD2.x compatibility with LyCORIS training
• Updated documentation to make multiGPU configuration a bit more obvious.
• Improved support for torch.compile(), including automatically disabling it when eg. fp8-quanto is enabled
  • Enable via accelerate config or config/config.env via TRAINER_DYNAMO_BACKEND=inductor
• TorchAO for quantisation as an alternative to Optimum Quanto for int8 weight-only quantisation (int8-torchao)
• f8uz-quanto, a compatibility level for AMD ROCm users to experiment with FP8 training dynamics
• Support for multigpu PEFT LoRA training with Quanto enabled (not fp8-quanto)
  • Previously, only LyCORIS would reliably work with quantised multigpu training sessions.
• Ability to quantise models when full-finetuning, without warning or error. Previously, this configuration was blocked. Your mileage may vary, it's an experimental configuration.

Integrations

• Images now get logged to tensorboard (thanks u/anhi)
• FastAPI endpoints for integrations (undocumented)
• "raw" webhook type that sends a large number of HTTP requests containing events, useful for push notification type service

Optims

• SOAP optimiser support
  • uses fp32 gradients, nice and accurate but uses more memory than other optims, by default slows down every 10 steps as it preconditions
• New 8bit and 4bit optimiser options from TorchAO (ao-adamw8bit, ao-adamw4bit etc)

Schnell

Recently we discovered that training LyCORIS LoKr on Flux.1 Dev works perfectly fine on Flux.1 Schnell at just 4 steps, and that the problems of transferring it over are specific to LoRA.

No special training is needed, other than to just train on Dev instead of Schnell.

The release:

The quickstart:

Some docs have been updated for v1.1, mostly OPTIONS.md and the FLUX quickstart.

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• Interesting find of the week: Kat, an engineer who built a tool to visualize time-based media with gestures.
• Flux updates:
  • Outpainting: ControlNet Outpainting using FLUX.1 Dev in ComfyUI demonstrated, with workflows provided for implementation.
  • Fine-tuning: Flux fine-tuning can now be performed with 10GB of VRAM, making it more accessible to users with mid-range GPUs.
  • Quantized model: Flux-Dev-Q5_1.gguf quantized model significantly improves performance on GPUs with 12GB VRAM, such as the NVIDIA RTX 3060.
  • New Controlnet models: New depth, upscaler, and surface normals models released for image enhancement in Flux.
  • CLIP and Long-CLIP models: Fine-tuned versions of CLIP-L and Long-CLIP models now fully integrated with the HuggingFace Diffusers pipeline.
• James Cameron joins Stability.AI: Renowned filmmaker James Cameron has joined Stability AI's Board of Directors, bringing his expertise in merging cutting-edge technology with storytelling to the AI company.
• Put This On Your Radar:
  • MIMO: Controllable character video synthesis model for creating realistic character videos with controllable attributes.
  • Google's Zero-Shot Voice Cloning: New technique that can clone voices using just a few seconds of audio sample.
  • Leonardo AI's Image Upscaling Tool: New high-definition image enlargement feature rivaling existing tools like Magnific.
  • PortraitGen: AI portrait video editing tool enabling multi-modal portrait editing, including text-based and image-based effects.
  • FaceFusion 3.0.0: Advanced face swapping and editing tool with new features like "Pixel Boost" and face editor.
  • CogVideoX-I2V Workflow Update: Improved image-to-video generation in ComfyUI with better output quality and efficiency.
  • Ctrl-X: New tool for image generation with structure and appearance control, without requiring additional training or guidance.
  • Invoke AI 5.0: Major update to open-source image generation tool with new features like Control Canvas and Flux model support.
  • JoyCaption: Free and open uncensored vision-language model (Alpha One Release) for training diffusion models.
  • ComfyUI-Roboflow: Custom node for image analysis in ComfyUI, integrating Roboflow's capabilities.
  • Tiled Diffusion with ControlNet Upscaling: Workflow for generating high-resolution images with fine control over details in ComfyUI.
  • 2VEdit: Video editing tool that transforms entire videos by editing just the first frame.
  • Flux LoRA showcase: New FLUX LoRA models including Simple Vector Flux, How2Draw, Coloring Book, Amateur Photography v5, Retro Comic Book, and RealFlux 1.0b.

📰 Full newsletter with relevant links, context, and visuals available in the original document.

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