Instructions to use layerdifforg/seethroughv0.0.1_marigold with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use layerdifforg/seethroughv0.0.1_marigold with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("layerdifforg/seethroughv0.0.1_marigold", 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
Claude Opus 5.5
Add Stable Diffusion 2 licence as the source of the use restrictions
4f4ffc4 verified Download NOTICE from layerdifforg/seethroughv0.0.1_marigold: direct link, hf CLI and curl.
- Browser
- Download file 1.91 kB
-
https://huggingface.co/layerdifforg/seethroughv0.0.1_marigold/resolve/main/NOTICE
- Command line
-
hf download hf://layerdifforg/seethroughv0.0.1_marigold/NOTICE
-
curl -L -o NOTICE https://huggingface.co/layerdifforg/seethroughv0.0.1_marigold/resolve/main/NOTICE
1.91 kB
| See-through: Marigold Depth | |
| Copyright 2026 The See-through Authors | |
| This model is part of See-through (https://github.com/shitagaki-lab/see-through). | |
| The See-through code is licensed under the Apache License, Version 2.0. | |
| The licence terms for these model weights are in LICENSE. | |
| ============================================================================== | |
| Third-party models | |
| ============================================================================== | |
| This model is derived from, or includes components of, the following: | |
| * Marigold Depth v1.1 by PRS, ETH Zürich. Copyright (c) 2023-2025 PRS, ETH Zürich. | |
| https://huggingface.co/prs-eth/marigold-depth-v1-1 | |
| Open RAIL++-M License | |
| The UNet was fine-tuned from this model. The VAE, text encoder and tokenizer | |
| are taken from it. | |
| * Stable Diffusion 2 by Stability AI. Copyright (c) 2022 Stability AI and contributors. | |
| CreativeML Open RAIL++-M License | |
| Base model of Marigold. The use-based restrictions in its Attachment A apply | |
| to this model. | |
| ============================================================================== | |
| Changes made by The See-through Authors | |
| ============================================================================== | |
| * The UNet was fine-tuned from Marigold Depth v1.1 for pseudo-depth estimation | |
| of anime characters, and converted into the multi-frame UNet | |
| (UNetFrameConditionModel) used by the See-through pipeline. | |
| * All components were saved in the diffusers format. | |
| ============================================================================== | |
| Citation | |
| ============================================================================== | |
| Jian Lin, Chengze Li, Haoyun Qin, Kwun Wang Chan, Yanghua Jin, Hanyuan Liu, | |
| Stephen Chun Wang Choy, and Xueting Liu. 2026. See-through: Single-image Layer | |
| Decomposition for Anime Characters. In SIGGRAPH Conference Papers '26. ACM. | |
| https://doi.org/10.1145/3799902.3811209 | |