Instructions to use xandergos/terrain-diffusion-autoencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xandergos/terrain-diffusion-autoencoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xandergos/terrain-diffusion-autoencoder", 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 config.json from xandergos/terrain-diffusion-autoencoder: direct link, hf CLI and curl.
- Browser
- Download file 476 Bytes
-
https://huggingface.co/xandergos/terrain-diffusion-autoencoder/resolve/main/config.json
- Command line
-
hf download hf://xandergos/terrain-diffusion-autoencoder/config.json
-
curl -L -o config.json https://huggingface.co/xandergos/terrain-diffusion-autoencoder/resolve/main/config.json
476 Bytes
| { | |
| "_class_name": "EDMAutoencoder", | |
| "_diffusers_version": "0.30.3", | |
| "attn_resolutions": [], | |
| "block_kwargs": null, | |
| "conditional_inputs": [], | |
| "direct_skips": [], | |
| "image_size": 512, | |
| "in_channels": 1, | |
| "latent_channels": 4, | |
| "layers_per_block": 2, | |
| "layers_per_block_decoder": null, | |
| "logvar_channels": 128, | |
| "midblock_attention": false, | |
| "model_channel_mults": [ | |
| 1, | |
| 2, | |
| 4, | |
| 4 | |
| ], | |
| "model_channels": 64, | |
| "n_logvar": 1, | |
| "out_channels": 1 | |
| } | |