Instructions to use Gazingstars123/Anima-2.9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusion Single File
How to use Gazingstars123/Anima-2.9B with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Questions about datasets
Hello! I am very optimistic about the future prospects of this model. Increasing the parameter count to 2.9b undoubtedly raises the upper limit of the model. However, I have some questions about the training set:
Will this model be added to high-level aesthetic datasets such as ArtStation in the future? On sdxl, chenkin noob used the full dan+artstation dataset, which gave the model an unparalleled aesthetic level compared to other sdxl models (making it my favorite sdxl model). Anima's textencoder and VAE have great advantages over sdxl, but to be honest, its aesthetics are somewhat sad compared to chenkin noob
In addition, ArtStation's dataset seems to have greatly enhanced the metallic texture, conceptual understanding ability, and light and shadow effects of Chenkin Noob
Certainly