first

README.md

@@ -89,7 +89,7 @@ pip install --upgrade git+https://github.com/huggingface/diffusers.git transform
 from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
 import torch
 
-model_id = "aipicasso/cool-japan-diffusion-2-1-0-beta"
+model_id = "aipicasso/cool-japan-diffusion-2-1-1-beta"
 
 scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
 pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.float16)

README_en.md

@@ -1,4 +1,4 @@
-# Cool Japan Diffusion 2.1.0 Model Card
+# Cool Japan Diffusion 2.1.1 Beta Model Card
 
 ![アイキャッチ](eyecatch.jpg)
 
@@ -16,4 +16,66 @@ TBA.
 # Usage
 You can try the model by our [Space](https://huggingface.co/spaces/alfredplpl/cool-japan-diffusion-2-1-0).
 I recommend to use the model by Web UI.
-You can download the model [here](https://huggingface.co/aipicasso/cool-japan-diffusion-2-1-0/resolve/main/v2-1-0.ckpt).
+You can download the model [here](https://huggingface.co/aipicasso/cool-japan-diffusion-2-1-0/resolve/main/v2-1-0.ckpt).
+
+## Model Details
+- **Developed by:** Robin Rombach, Patrick Esser, Alfred Increment
+- **Model type:** Diffusion-based text-to-image generation model
+- **Language(s):** English
+- **License:** [CreativeML Open RAIL++-M License](https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL)
+- **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [Latent Diffusion Model](https://arxiv.org/abs/2112.10752) that uses a fixed, pretrained text encoder ([OpenCLIP-ViT/H](https://github.com/mlfoundations/open_clip)).
+- **Resources for more information:** [GitHub Repository](https://github.com/Stability-AI/).
+- **Cite as:**
+
+      @InProceedings{Rombach_2022_CVPR,
+          author    = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn},
+          title     = {High-Resolution Image Synthesis With Latent Diffusion Models},
+          booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+          month     = {June},
+          year      = {2022},
+          pages     = {10684-10695}
+      }
+
+## Examples
+
+- Web UI
+- Diffusers
+
+## Web UI
+Download the model [here]().
+Then, install [Web UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) by AUTIMATIC1111.
+
+## Diffusers
+
+Using the [🤗's Diffusers library](https://github.com/huggingface/diffusers) to run Cool Japan Diffusion 2.1.1 Beta in a simple and efficient manner.
+
+```bash
+pip install --upgrade git+https://github.com/huggingface/diffusers.git transformers accelerate scipy
+```
+
+Running the pipeline (if you don't swap the scheduler it will run with the default DDIM, in this example we are swapping it to EulerDiscreteScheduler):
+
+```python
+from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
+import torch
+
+model_id = "aipicasso/cool-japan-diffusion-2-1-1-beta"
+
+scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
+pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
+
+prompt = "anime, a portrait of a girl with black short hair and red eyes, kimono, full color illustration, official art, 4k, detailed"
+negative_prompt="low quality, bad face, bad anatomy, bad hand, lowres, jpeg artifacts, 2d, 3d, cg, text"
+image = pipe(prompt,negative_prompt=negative_prompt).images[0]
+
+image.save("girl.png")
+
+```
+
+**Notes**:
+- Despite not being a dependency, we highly recommend you to install [xformers](https://github.com/facebookresearch/xformers) for memory efficient attention (better performance)
+- If you have low GPU RAM available, make sure to add a `pipe.enable_attention_slicing()` after sending it to `cuda` for less VRAM usage (to the cost of speed)
+
+
+*This model card was written by: Alfred Increment and is based on the [Stable Diffusion v2](https://huggingface.co/stabilityai/stable-diffusion-2/raw/main/README.md)