Image-to-Image
Diffusers
Safetensors
ZoomLDMPipeline
zoomldm
remote-sensing
naip
latent-diffusion
custom-pipeline
arxiv:2411.16969
Instructions to use BiliSakura/ZoomLDM-naip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/ZoomLDM-naip 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("BiliSakura/ZoomLDM-naip", 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
| { | |
| "target": "ldm.models.autoencoder.VQModelInterface", | |
| "params": { | |
| "embed_dim": 3, | |
| "n_embed": 8192, | |
| "ddconfig": { | |
| "double_z": false, | |
| "z_channels": 3, | |
| "resolution": 256, | |
| "in_channels": 3, | |
| "out_ch": 3, | |
| "ch": 128, | |
| "ch_mult": [ | |
| 1, | |
| 2, | |
| 4 | |
| ], | |
| "num_res_blocks": 2, | |
| "attn_resolutions": [], | |
| "dropout": 0.0 | |
| }, | |
| "lossconfig": { | |
| "target": "torch.nn.Identity" | |
| } | |
| } | |
| } |