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
Download model_index.json from layerdifforg/seethroughv0.0.1_marigold: direct link, hf CLI and curl.
- Browser
- Download file 499 Bytes
-
https://huggingface.co/layerdifforg/seethroughv0.0.1_marigold/resolve/main/model_index.json
- Command line
-
hf download hf://layerdifforg/seethroughv0.0.1_marigold/model_index.json
-
curl -L -o model_index.json https://huggingface.co/layerdifforg/seethroughv0.0.1_marigold/resolve/main/model_index.json
499 Bytes
| { | |
| "_class_name": "MarigoldDepthPipeline", | |
| "_diffusers_version": "0.37.0.dev0", | |
| "_name_or_path": "prs-eth/marigold-depth-v1-1", | |
| "default_denoising_steps": 4, | |
| "default_processing_resolution": 768, | |
| "scale_invariant": true, | |
| "scheduler": [ | |
| "diffusers", | |
| "DDIMScheduler" | |
| ], | |
| "shift_invariant": true, | |
| "text_encoder": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |