For version 1.0:

• This version was fine-tuned on Anima Base v1.0 using a variety of datasets, including Danbooru, e621, Gelbooru, and Konachan. The training approach differs from the original model in several ways. Most notably, I did not include quality score tags in the training data.
• I also experimented with multiple captioning styles, ranging from traditional tag-based annotations to different forms of natural language descriptions, similar to the approach I used for Netayume Lumina.
• Note:This release has two versions, each trained using different methods. For the v1.0 Demo, I experimented with a mixed training approach, but it was difficult to control. The v1.0 Final is different from the v1.0 Demo, so please don't compare them directly, even though they were trained on the same dataset. I created both versions to test different ideas for training diffusion models. Since Anima is small enough, it gives me the flexibility to experiment with various training methods and see what works best.Unlike Netayume, I did not use my full dataset for training. (The complete dataset contains around 25 million images, and if I were to use the entire dataset, I would train a model from scratch rather than fine-tune an existing one.) Additionally, I have been quite busy recently, so I have not been able to test this model as extensively as I would like. Moreover, this model dont have any default style :LV1.0 final has a watermark in the model, which is not effect the results of generated images. Moreover v1.0 currently support chain of though prompt as you can see in my example images i did it
• If you encounter any issues or have feedback, please feel free to share them with me.
• All example images were generated using prompts provi