Update README.md

README.md

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 ---
 license: other
+datasets:
+- Mitsua/vroid-image-dataset-lite
+library_name: diffusers
+pipeline_tag: text-to-image
 ---
+
+# Model Card for VRoid Diffusion Unconditional
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This is a latent unconditional diffusion model to demonstrate how U-Net training affects the generated images.
+
+- Text Encoder is removed. An empty text encoder is included for compatibility with stable diffusion.
+- VAE is from [Mitsua Diffusion One](https://huggingface.co/Mitsua/mitsua-diffusion-one), Mitsua Open RAIL-M License, Training Data: Public Domain/CC0 + Licensed
+- U-Net is trained from scratch using full version of [VRoid Image Dataset Lite](https://huggingface.co/datasets/Mitsua/vroid-image-dataset-lite) with some modifications.
+- VRoid is a trademark or registered trademark of Pixiv inc. in Japan and other regions.
+
+## Model variant
+- [VRoid Diffusion](https://huggingface.co/Mitsua/vroid-diffusion-test)
+  - This is conditional text-to-image generator using OpenCLIP.
+
+### Model Description
+
+- **Developed by:** Abstract Engine.
+- **License:** Mitsua Open RAIL-M License.
+
+## Uses
+
+### Direct Use
+
+Image generation for research and educational purposes.
+
+### Out-of-Scope Use
+
+Any deployed use case of the model.
+
+## Training Details
+
+- Trained resolution : 256x256
+- Batch Size : 48
+- Steps : 45k
+- LR : 1e-5 with warmup 1000 steps
+
+### Training Data
+
+We use full version of [VRoid Image Dataset Lite](https://huggingface.co/datasets/Mitsua/vroid-image-dataset-lite) with some modifications.