Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
landscape
Instructions to use CCMat/fforiver-river with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CCMat/fforiver-river 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", dtype=torch.bfloat16, device_map="cuda") prompt = "professional photo of fforiver river running alongside the Colosseum in Rome" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 134 Bytes
392cced | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:4897187f99613b8f87521a35f6cfb61c497c1bdfba92eca91498589328952f60
size 492309793
|