Update README.md

README.md

@@ -199,6 +199,7 @@ On Animagine XL 3.0, we mostly added characters from popular gacha games. Based
 
 ## Model Details
 - **Developed by**: [Cagliostro Research Lab](https://huggingface.co/cagliostrolab)
+- **Sponsored by** [Seaart](https://www.seaart.ai/)
 - **Model type**: Diffusion-based text-to-image generative model
 - **Model Description**: Animagine XL 3.1 is engineered to generate high-quality anime images from textual prompts. It features enhanced hand anatomy, better concept understanding, and prompt interpretation, making it the most advanced model in its series.
 - **License**: [Fair AI Public License 1.0-SD](https://freedevproject.org/faipl-1.0-sd/)
@@ -344,7 +345,7 @@ This model supports generating images at the following dimensions:
 
 - **Animagine XL 3.1** was trained on a 2x A100 GPU 80GB for roughly 15 days or over 350 gpu hours (pretraining stage). The training process encompassed three stages:
   - Continual Pretraining: 
-    - **Pretraining Stage**: Utilize data-rich collection of images, this consists of 870k million ordered, tagged images, to increase Animagine XL 3.0 model knowledge.
+    - **Pretraining Stage**: Utilize data-rich collection of images, this consists of 870k ordered, tagged images, to increase Animagine XL 3.0 model knowledge.
   - Finetuning: 
     - **First Stage**: Utilize labeled and curated aesthetic datasets to refine broken U-Net after pretraining
     - **Second Stage**: Utilize labeled and curated aesthetic datasets to refine the model's art style and fixing bad hands and anatomy
@@ -392,13 +393,15 @@ These limitations highlight areas for potential refinement in future iterations
 
 ## Acknowledgements
 
-We extend our gratitude to the entire team and community that contributed to the development of Animagine XL 3.0, including our partners and collaborators who provided resources and insights crucial for this iteration.
+We extend our gratitude to the entire team and community that contributed to the development of Animagine XL 3.0, including our partners and collaborators who provided resources and insights crucial for this iteration, and most importantly Seaart who provide compute power for model training. Without them we would not be able to Train this model properly.
 
-- **Main:** For the open source grant supporting our research, thank you so much.
+- **Main:** [Seaart](https://www.seaart.ai/) For the for the Sponsorship.
 - **Cagliostro Lab Collaborator:** For helping quality checking during pretraining and curating datasets during fine-tuning.
-- **Kohya SS:** For providing the essential training script and merged our PR about `keep_tokens_separator` or Shuffle Separator.
+- [**Kohya SS:**](https://github.com/bmaltais/kohya_ss) For providing the training scripts for model training, project, and data management
 - **Camenduru Server Community:** For invaluable insights and support and quality checking
-- **NovelAI:** For inspiring how to build the datasets and label it using tag ordering.
+- **NovelAI:** For inspiring how to build the datasets and label it using tag ordering and Aesthetic Tags
+- [**Shadow lilac:**](https://huggingface.co/shadowlilac/aesthetic-shadow-v2) For classification models.
+- [**Derrian Distro:**](https://github.com/derrian-distro/LoRA_Easy_Training_Scripts/blob/main/custom_scheduler/LoraEasyCustomOptimizer/CustomOptimizers.py) for lr scheduler
 
 ## Collaborators
 
@@ -409,6 +412,8 @@ We extend our gratitude to the entire team and community that contributed to the
 - [Zwicky18](https://huggingface.co/Zwicky18)
 - [Scipius2121](https://huggingface.co/Scipius2121)
 - [Raelina](https://huggingface.co/Raelina)
+- [Kayfahaarukku](https://huggingface.co/kayfahaarukku)
+- [Kristian](https://huggingface.co/Kr1SsSzz)
 
 ## License