Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use jkcarney/source4_v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jkcarney/source4_v1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jkcarney/source4_v1.0", 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:
- 3464a7db6305dd107693ca09358e262ac70afacef66c0cd4ef95a00901489e7b
- Size of remote file:
- 3.34 MB
- SHA256:
- dc3834aaef5416ddb387c8d1b5e73fb911c06a908e76ba447d555395115bfc4e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.