Instructions to use xandergos/terrain-diffusion-30m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xandergos/terrain-diffusion-30m 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-30m", 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
| { | |
| "_class_name": "EDMUnet2D", | |
| "_diffusers_version": "0.30.3", | |
| "_name_or_path": "checkpoints/models/consistency_decoder-64x3", | |
| "attn_resolutions": [], | |
| "block_kwargs": null, | |
| "concat_balance": 0.5, | |
| "conditional_inputs": [], | |
| "disable_out_gain": false, | |
| "emb_channels": null, | |
| "encode_only": false, | |
| "fourier_scale": "pos", | |
| "image_size": 512, | |
| "in_channels": 5, | |
| "layers_per_block": 3, | |
| "logvar_channels": 128, | |
| "midblock_attention": false, | |
| "model_channel_mults": [ | |
| 1, | |
| 2, | |
| 3, | |
| 4 | |
| ], | |
| "model_channels": 64, | |
| "n_logvar": 1, | |
| "noise_emb_dims": null, | |
| "out_channels": 1 | |
| } | |