Image-to-Image
Diffusers
StableDiffusionImageVariationPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use lambda/sd-image-variations-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lambda/sd-image-variations-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("lambda/sd-image-variations-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
Update scheduler/scheduler_config.json
#1
by patrickvonplaten - opened
scheduler/scheduler_config.json
CHANGED
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@@ -6,5 +6,6 @@
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"beta_start": 0.00085,
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"num_train_timesteps": 1000,
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"skip_prk_steps": true,
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"trained_betas": null
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}
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"beta_start": 0.00085,
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"num_train_timesteps": 1000,
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"skip_prk_steps": true,
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"trained_betas": null,
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"steps_offset": 1
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}
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