Instructions to use jingheya/lotus-depth-g-v1-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jingheya/lotus-depth-g-v1-0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jingheya/lotus-depth-g-v1-0", 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:
- 7c35686e7ab9a91c2c227cda47e90be48cffb1bd1751b0b88290b94797cbc764
- Size of remote file:
- 1.12 MB
- SHA256:
- 6a1d43efb57eb353b9297d1b28bea492773cece14e3ae7fab3e64bea83398b9c
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