Instructions to use PoolerSP/LogiLete with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PoolerSP/LogiLete 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("PoolerSP/LogiLete", 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 model_index.json
Browse files- model_index.json +6 -0
model_index.json
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{
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"model_type": "StableDiffusionInpaintPipeline",
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"pipeline": "stable-diffusion-inpainting",
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"base_model": "CompVis/stable-diffusion-v1-4",
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"license": "openrail++"
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}
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