Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
art
artistic
DreamlikeArt
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/DreamlikeDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/DreamlikeDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/DreamlikeDiffusion", 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
Commit History
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Adding `diffusers` weights of this model
Verified signatureThis PR adds fp32 and fp16 weights in PyTorch and safetensors format to Yntec/DreamlikeDiffusionf0f0364 -
Update scheduler/scheduler_config.json
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Update scheduler/scheduler_config.json
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Update scheduler/scheduler_config.json
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Update scheduler/scheduler_config.json
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Update scheduler/scheduler_config.json
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Adding `diffusers` weights of this model (#1)
Verified signature- Adding `diffusers` weights of this model (7ee563f366712a8882862c86be07e367ab0468cd)dc374bf