Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use digiplay/nk15_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use digiplay/nk15_diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("digiplay/nk15_diffusers", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| license: other | |
| tags: | |
| - stable-diffusion | |
| - stable-diffusion-diffusers | |
| - text-to-image | |
| - diffusers | |
| inference: true | |
| Model info: | |
| https://civitai.com/models/84604/nk15 | |
|  | |
| if you use this model in your diffusers, | |
| show some AutoencoderKL errors, | |
| Don't worry, just use the codes below, | |
| you can still generate images :) | |
| ``` | |
| modelid="digiplay/nk15_diffusers" | |
| from diffusers.models import AutoencoderKL | |
| vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse") | |
| pipe = DiffusionPipeline.from_pretrained(modelid, vae=vae) | |
| ``` | |
| DEMO image is generated by using diffusers + Google Colab | |