Ostris AI Toolkit has day zero support for training LoRAs on top of Baidu's ERNIE-Image
https://redd.it/1slivar
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https://redd.it/1slivar
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Media is too big
VIEW IN TELEGRAM
Tencent HY-World 2.0 appears to be dropping on April 15 — open-source multimodal 3D world generation from Tencent Hunyuan
https://redd.it/1sll638
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https://redd.it/1sll638
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New LTX model soon
https:\/\/x.com\/ltx\_model\/status\/2044110661488132371
link to their new paper too: https://doi.org/10.48550/arXiv.2604.11788
https://redd.it/1slh5rq
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https:\/\/x.com\/ltx\_model\/status\/2044110661488132371
link to their new paper too: https://doi.org/10.48550/arXiv.2604.11788
https://redd.it/1slh5rq
@rStableDiffusion
Nucleus-Image Released
https://huggingface.co/NucleusAI/Nucleus-Image
Nucleus-Image is a text-to-image generation model built on a sparse mixture-of-experts (MoE) diffusion transformer architecture. It scales to 17B total parameters across 64 routed experts per layer while activating only \~2B parameters per forward pass, establishing a new Pareto frontier in quality-versus-efficiency. Nucleus-Image matches or exceeds leading models including Qwen-Image, GPT Image 1, Seedream 3.0, and Imagen4 on GenEval, DPG-Bench, and OneIG-Bench. This is a base model released without any post-training optimization (no DPO, no reinforcement learning, no human preference tuning). All reported results reflect pre-training performance only. We release the full model weights, training code, and dataset, making Nucleus-Image the first fully open-source MoE diffusion model at this quality tier.
https://redd.it/1slpfch
@rStableDiffusion
https://huggingface.co/NucleusAI/Nucleus-Image
Nucleus-Image is a text-to-image generation model built on a sparse mixture-of-experts (MoE) diffusion transformer architecture. It scales to 17B total parameters across 64 routed experts per layer while activating only \~2B parameters per forward pass, establishing a new Pareto frontier in quality-versus-efficiency. Nucleus-Image matches or exceeds leading models including Qwen-Image, GPT Image 1, Seedream 3.0, and Imagen4 on GenEval, DPG-Bench, and OneIG-Bench. This is a base model released without any post-training optimization (no DPO, no reinforcement learning, no human preference tuning). All reported results reflect pre-training performance only. We release the full model weights, training code, and dataset, making Nucleus-Image the first fully open-source MoE diffusion model at this quality tier.
https://redd.it/1slpfch
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Reddit
From the StableDiffusion community on Reddit: Nucleus-Image Released
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Ernie for the Gooners
From my LIMITED tests so far with Ernie (bout an hour) - its about the same level as ZIT was when it released in terms of nudity.
Nipples pretty much 1 for 1 with ZIT - General nude breast shape seems better to me than zit when it came out
V*ginas = Nightmare fuel, unless a cl*toris the size of a thumb is your thing
P*nis = Nightmare fuel like zit, honestly even more funny but it defs understands the prompts better
Shape of the female parts are better. Prompting large breasts and small nipples give decent results, but its about the same as ZIT when it came out.
I think its more uncensored overall than ZIT, but well have to wait for the finetunes/lora training to be sure
https://redd.it/1slov4w
@rStableDiffusion
From my LIMITED tests so far with Ernie (bout an hour) - its about the same level as ZIT was when it released in terms of nudity.
Nipples pretty much 1 for 1 with ZIT - General nude breast shape seems better to me than zit when it came out
V*ginas = Nightmare fuel, unless a cl*toris the size of a thumb is your thing
P*nis = Nightmare fuel like zit, honestly even more funny but it defs understands the prompts better
Shape of the female parts are better. Prompting large breasts and small nipples give decent results, but its about the same as ZIT when it came out.
I think its more uncensored overall than ZIT, but well have to wait for the finetunes/lora training to be sure
https://redd.it/1slov4w
@rStableDiffusion
Reddit
From the StableDiffusion community on Reddit
Explore this post and more from the StableDiffusion community