Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Anime
Portrait
3D
Hius
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/Dreamful3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Dreamful3 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/Dreamful3", 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
This PR adds fp32 and fp16 weights in PyTorch and safetensors format to Yntec/Dreamful25f2cbbd -
Update text_encoder/config.json
88fad4c -
Adding `diffusers` weights of this model (#1)
- Adding `diffusers` weights of this model (9e471a22467e60b00cff447cec8060da7b11a702)1a6d7fa