text-to-image stable-diffusion

Dreambooth model trained by jorgecif with TheLastBen's fast-DreamBooth notebook

Test the model via A1111 Colab fast-Colab-A1111

Sample pictures of this concept:

<img src="https://huggingface.co/jorgecif/evoke-eva1/resolve/main/evapreview1.jpg" style="max-width: 200px;" width="100%"/>

<img src="https://huggingface.co/jorgecif/evoke-eva1/resolve/main/evapreview3.jpg" style="max-width: 200px;" width="100%"/>

<img src="https://huggingface.co/jorgecif/evoke-eva1/resolve/main/evapreview4.jpg" style="max-width: 200px;" width="100%"/>

<img src="https://huggingface.co/jorgecif/evoke-eva1/resolve/main/evapreview5.jpg" style="max-width: 200px;" width="100%"/>

CKPT

Download jorgeo.ckpt (2.13GB)

🧨 Diffusers

This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion Pipeline.

from diffusers import StableDiffusionPipeline
import torch

model_id = "dreamlike-art/dreamlike-photoreal-2.0"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "photo, a church in the middle of a field of crops, bright cinematic lighting, gopro, fisheye lens"
image = pipe(prompt).images[0]

image.save("./result.jpg")

License

This model is licesed under a modified CreativeML OpenRAIL-M license.