Stable Diffusion WebUI Forge (Forge) is a notable fork of SD WebUI started by Lvmin Zhang, who is also the creator of ControlNet and Fooocus. The initial goal of Forge was to improve the performance and features of SD WebUI with the intention to upstream changes back to SD WebUI. One of Forge's optimizations allowed users with low VRAM to generate images faster on some versions of Stable Diffusion. It improved generation speed for users with 8GB and 6GB VRAM by 30-45% and 60-75%, respectively. Forge also includes extra features such as support for more samplers than standard SD WebUI. Some of Forge's optimizations were borrowed from ComfyUI, and others were developed by the Forge team. In August 2024, Forge added support for the Flux diffusion model developed by Black Forest Labs, which is not yet supported by SD WebUI.
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Zhu, Andrew (2024). Using Stable Diffusion with Python: Leverage Python to control and automate high-quality AI image generation using Stable Diffusion. Packt Publishing. ISBN 978-1835084311. Stable Diffusion WebUI from AUTO MATIC1111: This might be the most popular web-based application currently that allows users to generate images and text using Stable Diffusion. It provides a GUI interface that makes it easy to experiment with different settings and parameters 978-1835084311
Brade, Stephen; Wang, Bryan; Sousa, Mauricio; Oore, Sageev; Grossman, Tovi (29 October 2023). "Promptify: Text-to-Image Generation through Interactive Prompt Exploration with Large Language Models". Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery. pp. 1–14. arXiv:2304.09337. doi:10.1145/3586183.3606725. ISBN 979-8-4007-0132-0. 979-8-4007-0132-0
Brade, Stephen; Wang, Bryan; Sousa, Mauricio; Oore, Sageev; Grossman, Tovi (29 October 2023). "Promptify: Text-to-Image Generation through Interactive Prompt Exploration with Large Language Models". Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery. pp. 1–14. arXiv:2304.09337. doi:10.1145/3586183.3606725. ISBN 979-8-4007-0132-0. 979-8-4007-0132-0
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Kim, Seonuk; Ko, Taeyoung; Kwon, Yousang; Lee, Kyungho (9 October 2023). "Designing interfaces for text-to-image prompt engineering using stable diffusion models: a human-AI interaction approach". IASDR Conference Series. doi:10.21606/iasdr.2023.448. ISBN 978-1-912294-59-6. 978-1-912294-59-6
Pocock, Kevin (16 August 2023). "Stable Diffusion: How to Use VAE". PC Guide. Retrieved 11 July 2024. https://www.pcguide.com/apps/how-to/stable-diffusion-how-to-use-vae/
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西川 和久 (14 February 2024). "【西川和久の不定期コラム】 VRAMが少ないGPUで画像生成AIを諦めていた人に。「Stable Diffusion WebUI Forge」登場!". PC Watch (in Japanese). https://pc.watch.impress.co.jp/docs/column/nishikawa/1568551.html
新清士 (February 26, 2024). "画像生成AI、安いPCでも高速に 衝撃の「Stable Diffusion WebUI Forge」 (1/4)". ASCII.jp (in Japanese). https://ascii.jp/elem/000/004/185/4185940/
西川 和久 (14 February 2024). "【西川和久の不定期コラム】 VRAMが少ないGPUで画像生成AIを諦めていた人に。「Stable Diffusion WebUI Forge」登場!". PC Watch (in Japanese). https://pc.watch.impress.co.jp/docs/column/nishikawa/1568551.html
新清士 (February 26, 2024). "画像生成AI、安いPCでも高速に 衝撃の「Stable Diffusion WebUI Forge」 (1/4)". ASCII.jp (in Japanese). https://ascii.jp/elem/000/004/185/4185940/
西川 和久 (14 February 2024). "【西川和久の不定期コラム】 VRAMが少ないGPUで画像生成AIを諦めていた人に。「Stable Diffusion WebUI Forge」登場!". PC Watch (in Japanese). https://pc.watch.impress.co.jp/docs/column/nishikawa/1568551.html
西川 和久 (14 February 2024). "【西川和久の不定期コラム】 VRAMが少ないGPUで画像生成AIを諦めていた人に。「Stable Diffusion WebUI Forge」登場!". PC Watch (in Japanese). https://pc.watch.impress.co.jp/docs/column/nishikawa/1568551.html
新清士 (February 26, 2024). "画像生成AI、安いPCでも高速に 衝撃の「Stable Diffusion WebUI Forge」 (1/4)". ASCII.jp (in Japanese). https://ascii.jp/elem/000/004/185/4185940/
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新清士 (February 26, 2024). "画像生成AI、安いPCでも高速に 衝撃の「Stable Diffusion WebUI Forge」 (1/4)". ASCII.jp (in Japanese). https://ascii.jp/elem/000/004/185/4185940/
田口和裕 (August 18, 2024). "話題の画像生成AI「FLUX.1」をStable Diffusion用の「WebUI Forge」で動かす(高速化も試してみました) (1/6)". ASCII.jp (in Japanese). https://ascii.jp/elem/000/004/215/4215695/