Instructions to use LogicGoInfotechSpaces/ObjectRemover with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LogicGoInfotechSpaces/ObjectRemover with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LogicGoInfotechSpaces/ObjectRemover", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cca44000153f1d39981d6695871d5a05b7c06a15d78131f0f65c7a7f237e9ecb
- Size of remote file:
- 56.7 MB
- SHA256:
- 1fba17b7886f87d9de5b406b399f14bb8e6146bf8dfd7646286fda17267e8032
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.