Instructions to use qian43/Sat3DGen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use qian43/Sat3DGen with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("qian43/Sat3DGen", 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: 1,255 Bytes
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"_class_name": "VAE_finetune",
"_diffusers_version": "0.35.1",
"decay": 0.9999,
"inv_gamma": 1.0,
"min_decay": 0.0,
"opt": {
"backbone": "dinov3-large-sat",
"network": {
"color_channels": 24,
"encoder3d": {
"hidden_dim": 4,
"mlp_ratio": 4,
"num_heads": 2,
"num_repeats": 16
},
"image_size": 256,
"latent_channel": 4,
"latent_size": 32,
"no_cls_token": true,
"no_hidden_states": true,
"point_sampling_kwargs": {
"aabb_strict": true,
"data_type": "vigor",
"num_importance": 48,
"num_points": 48
},
"position_scale_factor": 1,
"ray_marching_kwargs": {
"density_clamp_mode": "mipnerf",
"scale_color": false,
"use_mid_point": true,
"use_white_background": false
},
"sky": {},
"sr_factor": 2,
"triplane": {
"ch_mult": [
1,
2,
4,
4,
4
],
"dim": 32
}
},
"pad": 0.125,
"representation_type": "oneplane",
"sr_padding_mode": "reflect"
},
"optimization_step": 600000,
"power": 0.6666666666666666,
"update_after_step": 0,
"use_ema_warmup": false
}
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