| | --- |
| | license: apache-2.0 |
| | --- |
| | |
| |
|
| | ### china-chic-style on stable diffuison by dreambooth |
| |
|
| | Here are the images used for training this concept: |
| |
|
| |  |
| |
|
| |  |
| |
|
| |  |
| |
|
| |
|
| | #### new concept |
| |
|
| | china-chic-style |
| |
|
| | #### inference |
| |
|
| | ```` |
| | from torch import autocast |
| | from diffusers import StableDiffusionPipeline |
| | import torch |
| | import diffusers |
| | from PIL import Image |
| | |
| | |
| | def image_grid(imgs, rows, cols): |
| | assert len(imgs) == rows*cols |
| | w, h = imgs[0].size |
| | grid = Image.new('RGB', size=(cols*w, rows*h)) |
| | grid_w, grid_h = grid.size |
| | for i, img in enumerate(imgs): |
| | grid.paste(img, box=(i%cols*w, i//cols*h)) |
| | return grid |
| | |
| | |
| | pipe = StableDiffusionPipeline.from_pretrained("Dushwe/china-chic-landscape").to("cuda") |
| | prompt = 'the moon hanging high in the sky,chinc-chic-style' |
| | images = pipe(prompt, num_images_per_prompt=1, num_inference_steps=50, guidance_scale=7.5,torch_dtype=torch.cuda.HalfTensor).images |
| | grid = image_grid(images, 1, 1) |
| | grid |
| | ```` |
| |  |
| |
|
| |
|
| |
|
| | You run your new concept via `diffusers` |
| | [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb). Don't forget to use the concept prompts! |
| |
|
| |
|