Instructions to use bart1259/CityDiffusion2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bart1259/CityDiffusion2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bart1259/CityDiffusion2", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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Download README.md from bart1259/CityDiffusion2: direct link, hf CLI and curl.
- Browser
- Download file 217 Bytes
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https://huggingface.co/bart1259/CityDiffusion2/resolve/main/README.md
- Command line
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hf download hf://bart1259/CityDiffusion2/README.md
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curl -L -o README.md https://huggingface.co/bart1259/CityDiffusion2/resolve/main/README.md
217 Bytes
| license: mit | |
| datasets: | |
| - bart1259/netherlands_512_2m | |
| pipeline_tag: image-to-image | |
| tags: | |
| - Diffusion | |
| - City | |
| - Generation | |
| # City Diffusion 2 | |
| Check it out on [GitHub](https://github.com/bart1259/CityDiffusion2) |