Instructions to use GraydientPlatformAPI/deli6-in with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GraydientPlatformAPI/deli6-in with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import AutoPipelineForInpainting from diffusers.utils import load_image # switch to "mps" for apple devices pipe = AutoPipelineForInpainting.from_pretrained("GraydientPlatformAPI/deli6-in", dtype=torch.float16, device_map="cuda") img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png" mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png" image = load_image(img_url).resize((1024, 1024)) mask_image = load_image(mask_url).resize((1024, 1024)) prompt = "a tiger sitting on a park bench" generator = torch.Generator(device="cuda").manual_seed(0) image = pipe( prompt=prompt, image=image, mask_image=mask_image, guidance_scale=8.0, num_inference_steps=20, # steps between 15 and 30 work well for us strength=0.99, # make sure to use `strength` below 1.0 generator=generator, ).images[0] - Notebooks
- Google Colab
- Kaggle
Download vae/diffusion_pytorch_model.safetensors from GraydientPlatformAPI/deli6-in: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/GraydientPlatformAPI/deli6-in/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://GraydientPlatformAPI/deli6-in/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/GraydientPlatformAPI/deli6-in/resolve/main/vae/diffusion_pytorch_model.safetensors
167 MB
- Xet hash:
- d0497a7adfc9b84d34efa711cc3e53a50648a19e62daff5fc939f00df568b893
- Size of remote file:
- 167 MB
- SHA256:
- 577abdb29d0ca00d00481475c336cb4db5f13a0ea5b254c65c48f10cf406161d
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