Instructions to use S1T4L/Zero123pp_custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use S1T4L/Zero123pp_custom with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("S1T4L/Zero123pp_custom", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download feature_extractor_vae/preprocessor_config.json from S1T4L/Zero123pp_custom: direct link, hf CLI and curl.
- Browser
- Download file 369 Bytes
-
https://huggingface.co/S1T4L/Zero123pp_custom/resolve/main/feature_extractor_vae/preprocessor_config.json
- Command line
-
hf download hf://S1T4L/Zero123pp_custom/feature_extractor_vae/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/S1T4L/Zero123pp_custom/resolve/main/feature_extractor_vae/preprocessor_config.json
369 Bytes
| { | |
| "crop_size": { | |
| "height": 512, | |
| "width": 512 | |
| }, | |
| "do_center_crop": true, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": 0.5, | |
| "image_processor_type": "CLIPImageProcessor", | |
| "image_std": 0.8, | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 512 | |
| } | |
| } | |