Instructions to use YiYiXu/modular-diffdiff-0704 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YiYiXu/modular-diffdiff-0704 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YiYiXu/modular-diffdiff-0704", 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
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Download README.md from YiYiXu/modular-diffdiff-0704: direct link, hf CLI and curl.
- Browser
- Download file 1.27 kB
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https://huggingface.co/YiYiXu/modular-diffdiff-0704/resolve/a2d37e0e80098e3e88e656b9e0a66f2e4259a10b/README.md
- Command line
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hf download hf://YiYiXu/modular-diffdiff-0704@a2d37e0e80098e3e88e656b9e0a66f2e4259a10b/README.md
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curl -L -o README.md https://huggingface.co/YiYiXu/modular-diffdiff-0704/resolve/a2d37e0e80098e3e88e656b9e0a66f2e4259a10b/README.md
1.27 kB
| license: apache-2.0 | |
| library_name: diffusers | |
| test under this PR https://github.com/huggingface/diffusers/pull/11235 | |
| ```python | |
| from diffusers.modular_pipelines import ModularPipeline, ComponentsManager | |
| import torch | |
| from diffusers.utils import load_image | |
| repo_id = "YiYiXu/modular-diffdiff" | |
| components = ComponentsManager() | |
| diffdiff_pipeline = ModularPipeline.from_pretrained(repo_id, trust_remote_code=True, component_manager=components, collection="diffdiff") | |
| diffdiff_pipeline.load_componenets(torch_dtype=torch.float16) | |
| components.enable_auto_cpu_offload() | |
| image = load_image( "https://huggingface.co/datasets/OzzyGT/testing-resources/resolve/main/differential/20240329211129_4024911930.png?download=true") | |
| mask = load_image("https://huggingface.co/datasets/OzzyGT/testing-resources/resolve/main/differential/gradient_mask.png?download=true") | |
| prompt = "a green pear" | |
| negative_prompt = "blurry" | |
| image = diffdiff_pipeline( | |
| prompt=prompt, | |
| negative_prompt=negative_prompt, | |
| num_inference_steps=25, | |
| diffdiff_map=mask, | |
| image=image, | |
| output="images" | |
| )[0] | |
| image.save("yiyi_test_modular_remote_diffdiff_out.png") | |
| ``` | |
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