Instructions to use xandergos/terrain-diffusion-90m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xandergos/terrain-diffusion-90m 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-90m", 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
File size: 612 Bytes
e96ebc7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"_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
}
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