description: <p><strong><span style="color:rgb(250, 82, 82)">v4.0 My best version so far. Still 8 dim, very good similarity, better picture quality than before, and I believe it is not inferior to any other large lora with 64/128 dim on this site.</span></strong></p><p><span style="color:rgb(250, 82, 82)">This time I trained with 8x8 batch size (using gradient accumulation), a high lr and I trained text encoder this time. Seems like you just have to use a lower te lr than unet.</span></p><p>Let me know if there are any other characters you would like me to train.</p><p>v3.0: Still 8 dim, can't really say this version is a lot better, but it's an interesting alt choice. With less dataset, more epochs. I personally believe that it achieves good flexibility.</p><p>v2.0 update: Yes, I proved it. <strong><span style="color:rgb(250, 82, 82)">Even 8 dim is enough.</span></strong></p><p><strong><span style="color:rgb(250, 82, 82)">STOP UPLOADING HUGE 128 or 256 dim LORAs.</span></strong></p><p>p.s. I've already replaced it with 30 epoch ver, which is basically better than 12 ep.</p><p>I trained this lora to show one thing:<br /><strong><span style="color:rgb(250, 82, 82)">You don't need a HUGE lora to recreate a real person. 16 dim is more than enough.</span></strong><br />Too many SDXL loras in this site now take too much size. Size of a full SDXL model is about 6-7 GB, and some lora takes <strong>1.7 GB</strong>? <strong>Outrageous</strong>.</p><p>Stop training real person loras with more than 32 dim... It's a waste of training time and disk space. Single anime character could use less than 8 dim. Save your time. Save bandwidth for this site.</p><p><br />Anyway, my lora here takes ~200 images and ~1 hour to train. 1 repeat, 42 epoch for this one. Its simple to use, just use the name. It took me no more than 2 hours from gathering the images and captioning to training.</p><p>The key is, use a proper VLM to generate caption for your dataset, like LLaVA or CogVLM, or better, GPT4v. Use natural language cause it works good on SDXL. Do not train text encoders.<br />For people or characters already known by the base model, DO NOT use a seperate trigger token. SDXL knows who Ana de Armas is, so as Taylor Swift, Jenna Ortega... NEVER use something like "ohwx".<br />For those who weren't in the base model, it's good enough to use their names as trigger token. The model could tell something from their name, like race, nationality...<br />Feel free to tell me how you think in the comment.</p><p></p><p>My preview images were generated with ComfyUI. You could download them and load them in ComfyUI to load my workflow.</p>
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name: Ana de Armas - SDXL 8 dim ver: NO MORE HUGE LORAs.
tags: ana de armas woman celeb