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update changelog

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Vladimir Mandic
2024-08-31 11:57:10 -04:00
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CHANGELOG.md
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# Change Log for SD.Next
## Update for 2024-08-29
## Update for 2024-08-31
### Highlights for 2024-08-29
### Highlights for 2024-08-31
Summer break is over and we are back with a massive update!
Support for all of the new models:
- [Black Forest Labs FLUX.1](https://blackforestlabs.ai/announcing-black-forest-labs/)
- [AuraFlow](https://huggingface.co/fal/AuraFlow)
- [AuraFlow 0.3](https://huggingface.co/fal/AuraFlow)
- [AlphaVLLM Lumina-Next-SFT](https://huggingface.co/Alpha-VLLM/Lumina-Next-SFT-diffusers)
- [Kwai Kolors](https://huggingface.co/Kwai-Kolors/Kolors)
- [HunyuanDiT 1.2](https://huggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers)
What else? Just a bit... ;)
New **fast-install** mode, new **Optimum Quanto** and **BitsAndBytes** quantization modes, new **balanced offload** mode, new **ControlNet-Union** *all-in-one* model, support for **DoRA** networks, additional **VLM** models, new **AuraSR** upscaler, and more...
New **fast-install** mode, new **Optimum Quanto** and **BitsAndBytes** based quantization modes, new **balanced offload** mode that dynamically offloads GPU<->CPU as needed, and more...
And from previous service-pack: new **ControlNet-Union** *all-in-one* model, support for **DoRA** networks, additional **VLM** models, new **AuraSR** upscaler
**Breaking Changes...**
Due to internal changes, you'll need to reset your **attention** and **offload** settings!
But...For a good reason, new *balanced offload* is magic when it comes to memory utilization while sacrificing minimal performance!
### Details for 2024-08-29
### Details for 2024-08-31
**New Models...**
@@ -31,7 +32,7 @@ To use and of the new models, simply select model from *Networks -> Reference* a
- [Black Forest Labs FLUX.1](https://blackforestlabs.ai/announcing-black-forest-labs/)
FLUX.1 models are based on a hybrid architecture of multimodal and parallel diffusion transformer blocks, scaled to 12B parameters and builing on flow matching
This is a very large model at ~32GB in size, its recommended to use a) offloading, b) quantization
For more information on how to donwload and use FLUX.1, see [Wiki](https://github.com/vladmandic/automatic/wiki/FLUX)
For more information on variations, requirements, options, and how to donwload and use FLUX.1, see [Wiki](https://github.com/vladmandic/automatic/wiki/FLUX)
SD.Next supports:
- [FLUX.1 Dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) and [FLUX.1 Schnell](https://huggingface.co/black-forest-labs/FLUX.1-schnell) original variations
- additional [qint8](https://huggingface.co/Disty0/FLUX.1-dev-qint8) and [qint4](https://huggingface.co/Disty0/FLUX.1-dev-qint4) quantized variations