Text-to-Image
Diffusers
Safetensors
English
remote-sensing
earth-observation
satellite-imagery
flow-matching
diffusion-transformer
geospatial
Instructions to use BiliSakura/GeoCore-9B-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/GeoCore-9B-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/GeoCore-9B-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "A parking lot full of cars is located next to some trees." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 494 Bytes
89d4944 | 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 | {
"_class_name": "GeoCoreTransformer2DModel",
"_diffusers_version": "0.32.0",
"in_channels": 128,
"context_in_dim": 4096,
"hidden_size": 4096,
"num_heads": 32,
"depth": 8,
"depth_repa": 8,
"depth_single_blocks": 24,
"axes_dim": [
32,
48,
48
],
"theta": 2000,
"mlp_ratio": 3.0,
"y_in_dim": 768,
"z_out_dim": 4096,
"model_size": "9b",
"sample_size": 16,
"patch_size": 2,
"latent_channels": 128,
"weights": "model",
"training_steps": 300000
}
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