description: <h3 id="heading-359">This model can only be used with both embeddings and LoRAs so you must also download the embeddings from what I mark as "training data"</h3><p>Using only the LoRA is not effective (civitai however does not allow to upload zip directly for LoRA. I will eventually upload the bundle format once it is supported in webui). The zip containing both lora and embeddings can otherwise be downloaded here <a target="_blank" rel="ugc" href="https://huggingface.co/alea31415/YuriDiffusion/blob/main/gekidol/gekidol-civitai.zip">https://huggingface.co/alea31415/YuriDiffusion/blob/main/gekidol/gekidol-civitai.zip</a></p><p><br />This model uses pivotal tuning as explained in <a target="_blank" rel="ugc" href="https://civitai.com/articles/2494/making-better-loras-with-pivotal-tuning">https://civitai.com/articles/2494/making-better-loras-with-pivotal-tuning</a></p><p>The data construction workflow follows <a target="_blank" rel="ugc" href="https://civitai.com/articles/2383/a-99percent-automatized-pipeline-to-construct-character-pack-training-set-from-anime">https://civitai.com/articles/2383/a-99percent-automatized-pipeline-to-construct-character-pack-training-set-from-anime</a></p><p>All intermediate checkpoints and pts available at: <a target="_blank" rel="ugc" href="https://huggingface.co/alea31415/YuriDiffusion/tree/main/gekidol">https://huggingface.co/alea31415/YuriDiffusion/tree/main/gekidol</a></p><p><br />Pivotal tuning trains embeddings and the network in the same time. For this model the content of the zip file is (no more LoRA in the zip downloaded here)</p><p><img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/7674e987-216e-4456-9d96-f4fecb47c92a/width=525/7674e987-216e-4456-9d96-f4fecb47c92a.jpeg" /></p><p></p><p>You need to put the LoRA in LoRA folder, pts in embedding folders, and the txt file can be used with <a target="_blank" rel="ugc" href="https://github.com/adieyal/sd-dynamic-prompts">https://github.com/adieyal/sd-dynamic-prompts</a> and <a target="_blank" rel="ugc" href="https://github.com/DominikDoom/a1111-sd-webui-tagcomplete">https://github.com/DominikDoom/a1111-sd-webui-tagcomplete</a> for easier prompting.</p><p></p><p>This is a temporary solution. The bundle system will allow much easier usage of results obtained from pivotal tuning. See <a target="_blank" rel="ugc" href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/13568">https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/13568</a></p><h2 id="heading-3145"></h2><h3 id="heading-3146">About the model</h3><p>Honestly, I do not particularly expect people to use the model.</p><ol><li><p>Gekidol is a very unpopular anime, but a good one (well ... I suppose). I take this opportunity to do some promotion for it.</p></li><li><p>The model is trained on <a target="_blank" rel="ugc" href="https://huggingface.co/Crosstyan/BPModel">https://huggingface.co/Crosstyan/BPModel</a>. Normally this makes it work less well on popular models although this is less the case here thanks to pivotal tuning. BPModel has its benefit, for those who know what it is for 😉. (And yes, as what I usually do, you can still use other LoRAs or build merge on top of it.)</p></li><li><p>As explained, the current ecosystem is not friendly enough for this kind of setup.</p></li></ol><p></p><p>If you happen to want to use the model, here are some important associations</p><ul><li><p>Seria: yellow hairband</p></li><li><p>Mayuri: hairband</p></li><li><p>Manami: glasses</p></li><li><p>Izumi: hair scrunchie (and as usual the model cannot tell left from right)</p></li></ul><p></p><p>---</p><p>I plan to completely shift to pivotal tuning once the bundle system is incorporated and LyCORIS is supported in HCP-Diffusion. As you can see, this model has a quite strong anime styles, which for me is related to the use of LoRA instead of LoHa here.</p>
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name: GekiDol ゲキドル - LoRA Pivotal Tuning || Airi / Seria / Izumi / Doll / Akira / Manami / Mayuri / Kazeharu / Tomoko / Kaworu / ...
tags: anime character multi-character characterpack pivotal-tuning