Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
photorealistic
photoreal
art
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/Dreamlike with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Dreamlike 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/Dreamlike", 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
Download vae/diffusion_pytorch_model.bin from Yntec/Dreamlike: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/Yntec/Dreamlike/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Yntec/Dreamlike@refs/pr/1/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Yntec/Dreamlike/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 9e0678c40a8210d9a359c1d2fb29f0e1308d899d5b4e9e1835a38704d2bc2111
- Size of remote file:
- 335 MB
- SHA256:
- 818ae65e8ded5548b34f6d6f01c1a99b961f1af9197d0f746ca090618f74a549
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