Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
landscape
Instructions to use CCMat/fruins-ruins with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CCMat/fruins-ruins 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/fruins-ruins", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of fruins ruins in Paris in front of the Arc de triomphe, mdjrny-v4 style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
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Librarian Bot: Update dataset YAML metadata for model
This is a pull request to add a dataset, [`CCMat/db-forest-ruins`](https://huggingface.co/datasets/CCMat/db-forest-ruins), to the metadata for your model (defined in the `YAML` block of your model's `README.md`). The pull request was made by [librarian-bot](https://huggingface.co/librarian-bot) and used a combination of rules and/or machine learning to suggest this additional metadata. If this suggestion is incorrect, feel free to close this pull request. Librarian Bot was made by [@davanstrien](https://huggingface.co/davanstrien); feel free to get in touch with feedback.2071de0
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Add `scale_factor` to vae config. (#1)
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