Instructions to use YuCollection/sdxl-1.0-refiner-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YuCollection/sdxl-1.0-refiner-diffusers 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("YuCollection/sdxl-1.0-refiner-diffusers", 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
Upload scheduler/scheduler_config.json with huggingface_hub
Browse files
scheduler/scheduler_config.json
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{
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"_class_name": "EulerDiscreteScheduler",
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"_diffusers_version": "0.19.0.dev0",
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"beta_end": 0.012,
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"beta_schedule": "scaled_linear",
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"beta_start": 0.00085,
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"clip_sample": false,
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"interpolation_type": "linear",
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"num_train_timesteps": 1000,
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"prediction_type": "epsilon",
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"sample_max_value": 1.0,
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"set_alpha_to_one": false,
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"skip_prk_steps": true,
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"steps_offset": 1,
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"timestep_spacing": "leading",
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"trained_betas": null,
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"use_karras_sigmas": false
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}
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