Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
landscape
Instructions to use CCMat/fforiver-river-mdj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CCMat/fforiver-river-mdj with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CCMat/fforiver-river-mdj", dtype=torch.bfloat16, device_map="cuda") prompt = "Fallout concept of fforiver river in front of the Great Pyramid of Giza" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Add `scale_factor` to vae config. (#1)
- Add `scale_factor` to vae config. (c36243b0387657a23aa51d7dab773a7d0049019d) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>ff723bb
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