■This is an experimental ground for Anima LoRAs.The LoRAs I create serve more of a role in stylistic tuning rather than reinforcing single concepts.There is no inherent superiority among the LoRAs; they simply serve different purposes. You can find the description for each LoRA in its respective tab.■If you notice pixel patterns in your generated images, try the VAE below. It removes the pixelation typical of the qwen_vae and makes the images much sharper.<a target="_blank" rel="ugc" href="https://civarchive.com/models/2718533/hdr-vae-anima-qwen-image">https://civarchive.com/models/2718533/hdr-vae-anima-qwen-image</a>■If the VAE looks a bit too saturated for your taste, try using this VAE merge node to blend it with the original qwen_vae to dial it in. A 0.5 merge should be just right.<a target="_blank" rel="ugc" href="https://civarchive.com/models/2487550/vae-merger-for-comfyui-anima">https://civarchive.com/models/2487550/vae-merger-for-comfyui-anima</a>■I would like to share the possibilities of anima with everyone.My wish is for many people to discover basemodels with potential and to see their possibilities unfold even further. I would be happy if I can help make that happen.■The anima architecture has been heavily modified and retrained from scratch—almost like a radical overhaul—but the base architecture is Cosmos-Predict2-2B. To put it simply, you could compare it to a lightweight version of Flux 1.I think it’s a great architecture capable of generating high-quality images despite its small size.I have a very good impression of Anima when it comes to color vibrancy, lighting, and prompt adherence.Its knowledge regarding NSFW concepts, characters, and styles is at least on par with SDXL. The overall feel of using it is also quite similar to SDXL.Furthermore, it is lightweight and easy to train. I believe large-scale training is also a viable option.Since we are provided with a base model that already contains a vast amount of knowledge, we rarely need to teach the model completely unknown concepts from scratch.Basically, our work mostly comes down to adjusting styles or reinforcing minor concepts and characters. You can achieve great results without having to do any heavy lifting.The developer has also ensured transparency by sharing the training settings, which means you are less likely to stumble over black-box issues.Because of this, the burden of training is low, making it an option well worth nurturing together as a community.■The LoRA has a stronger influence when used with shorter prompts.Since longer prompts often carry their own inherent style, the LoRA will primarily take on a supporting role to refine and unify the overall image.■<a target="_blank" rel="ugc" href="https://github.com/gazingstars123/Anima-Standalone-Trainer">https://github.com/gazingstars123/Anima-Standalone-Trainer</a>This is a great tool that allows for easy training, even on Windows. It has everything you need for LoRA training.Even if you run into any issues, you should be able to get your LoRA training up and running by troubleshooting with ChatGPT or Gemini.If you find the tool useful, you might want to consider making a donation to him. It allows the developer to focus more on development and deliver even better tools, which ultimately benefits you in the long run.■If you have any questions, please feel free to ask!日本語での質問も大丈夫ですのでご気軽にお声がけください～If you enjoy my work and feel like making a donation, I would be incredibly grateful. Even the smallest token of support goes a long way in helping me lighten the load.Whether I receive donations or not, I will keep doing what I love and pursuing my interests just as I always have. However, simply knowing that this kind of support exists brings me immense joy and serves as a huge driving force for me.<a target="_blank" rel="ugc" href="https://ko-fi.com/meg481074">https://ko-fi.com/meg481074</a>

anima_lora_lab

This is an aesthetic LoRA for Anima-Base-v1.0, trained on 1,618 aesthetic 2D-style images.Style Tendencies:This LoRA has a strong tendency to generate a flat, low-contrast 2D style. The dataset itself heavily leans toward this aesthetic, and I deliberately excluded any 3D, volumetric, or realistic images. As a result, you will often notice a distinct hand-drawn vibe in the generations.Backup Versions (Different Steps):While the main version is the 1,500-step LoRA, I have also included a few backup versions trained up to 3,250 steps. These backups are trained further, which significantly shifts the style—resulting in a much cleaner and more subdued/calm aesthetic. If you find you aren't a fan of the main LoRA's style, I highly recommend giving these a try.The step count is low, but with an effective batch size of 32, it's actually trained quite a bit.Dataset Size:The reason the dataset is relatively small this time is that I had a very specific 2D style goal I wanted to achieve, so I intentionally curated only images with similar stylistic tendencies. Normally, my goal is to train the model on a wide variety of aesthetic styles, which explains the difference in dataset size compared to my usual releases. You can find the workflow either inside <code>loras.zip</code> or inside <code>anima_workflow.zip</code> located under the <code>anime_aesthetic_v2_pre3</code> tab.

Files with SHA256: be54f500cea0fb863b5ba6d9b624be82ac873b531fe4bda5cce4dc386fb6c580