Instructions to use LetsThink/RORem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LetsThink/RORem 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("LetsThink/RORem", 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 text_encoder/model.safetensors from LetsThink/RORem: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/LetsThink/RORem/resolve/main/text_encoder/model.safetensors
- Command line
-
hf download hf://LetsThink/RORem/text_encoder/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/LetsThink/RORem/resolve/main/text_encoder/model.safetensors
246 MB
- Xet hash:
- cab029ae94ceea1ea4932e78c51ceb6da01e25edb0c27f94005391f16198c36e
- Size of remote file:
- 246 MB
- SHA256:
- 660c6f5b1abae9dc498ac2d21e1347d2abdb0cf6c0c0c8576cd796491d9a6cdd
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