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
Upload 2 files
Browse filesSat3DGen_ICLR2026_weight
- config.json +56 -0
- diffusion_pytorch_model.safetensors +3 -0
config.json
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{
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"_class_name": "VAE_finetune",
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"_diffusers_version": "0.35.1",
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"decay": 0.9999,
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"inv_gamma": 1.0,
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"min_decay": 0.0,
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"opt": {
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"backbone": "dinov3-large-sat",
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"network": {
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"color_channels": 24,
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"encoder3d": {
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"hidden_dim": 4,
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"mlp_ratio": 4,
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"num_heads": 2,
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"num_repeats": 16
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},
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"image_size": 256,
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"latent_channel": 4,
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"latent_size": 32,
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"no_cls_token": true,
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"no_hidden_states": true,
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"point_sampling_kwargs": {
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"aabb_strict": true,
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"data_type": "vigor",
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"num_importance": 48,
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"num_points": 48
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},
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"position_scale_factor": 1,
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"ray_marching_kwargs": {
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"density_clamp_mode": "mipnerf",
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"scale_color": false,
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"use_mid_point": true,
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"use_white_background": false
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},
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"sky": {},
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"sr_factor": 2,
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"triplane": {
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"ch_mult": [
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1,
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2,
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4,
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4,
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4
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],
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"dim": 32
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}
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},
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"pad": 0.125,
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"representation_type": "oneplane",
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"sr_padding_mode": "reflect"
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},
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"optimization_step": 600000,
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"power": 0.6666666666666666,
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"update_after_step": 0,
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"use_ema_warmup": false
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}
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diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8770de3ea777d586160036a78d29bd8f1cc2ae2d1d9900f01945c6c8f4377846
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size 1524183560
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