Instructions to use Niggendar/thisCameToMeInADream_mid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Niggendar/thisCameToMeInADream_mid with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Niggendar/thisCameToMeInADream_mid", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 6abaa3002f45ff9895b616a0649d400c793b44449360f825b2f683cbe7e098bb
- Size of remote file:
- 246 MB
- SHA256:
- 9c1c0da61f4c7f4258e04acc3000bd0fd15b7aecfff6efe84b25b2559089ba00
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.