BiliSakura / EO-VAE

huggingface.co
Total runs: 29
24-hour runs: 0
7-day runs: -12
30-day runs: -11
Model's Last Updated: February 16 2026
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Introduction of EO-VAE

Model Details of EO-VAE

EO-VAE

Earth Observation Variational Autoencoder. Self-contained, no external eo-vae package—uses only torch , safetensors , and huggingface_hub .

Usage
from huggingface_hub import snapshot_download
import sys
import torch

model_dir = snapshot_download("BiliSakura/EO-VAE")
sys.path.insert(0, model_dir)
from eo_vae import EOVAEModel, WAVELENGTHS

vae = EOVAEModel.from_pretrained(model_dir, torch_dtype=torch.float32, device="cpu")

x = torch.randn(1, 3, 256, 256)
wvs = torch.tensor(WAVELENGTHS["S2RGB"], dtype=torch.float32)
with torch.no_grad():
    recon = vae.reconstruct(x, wvs)
    z = vae.encode_spatial_normalized(x, wvs)  # [1, 32, 32, 32]
Model
Property Value
Architecture Flux-style VAE with wavelength-conditioned dynamic convolutions
Input [B, C, 256, 256] + wavelengths [C]
Latent [B, 32, 32, 32] (spatial) or [B, 128, 16, 16] (packed)
Modalities S2RGB, S2L2A, S1RTC, S1GRD
Wavelengths (µm)
Modality Values
S2RGB 0.665, 0.56, 0.49
S1RTC 5.4, 5.6
S2L2A 0.443, 0.490, 0.560, 0.665, 0.705, 0.740, 0.783, 0.842, 0.865, 1.610, 2.190, 0.945
S2L1C 0.443, 0.490, 0.560, 0.665, 0.705, 0.740, 0.783, 0.842, 0.865, 0.945, 1.375, 1.610, 2.190
Citation
@article{eo-vae,
  title={EO-VAE: Towards A Multi-sensor Tokenizer for Earth Observation Data},
  author={Lehmann, Nils and Wang, Yi and Xiong, Zhitong and Zhu, Xiaoxiang},
  journal={arXiv preprint arXiv:2602.12177},
  year={2026}
}

Runs of BiliSakura EO-VAE on huggingface.co

29
Total runs
0
24-hour runs
0
3-day runs
-12
7-day runs
-11
30-day runs

More Information About EO-VAE huggingface.co Model

EO-VAE huggingface.co

EO-VAE huggingface.co is an AI model on huggingface.co that provides EO-VAE's model effect (), which can be used instantly with this BiliSakura EO-VAE model. huggingface.co supports a free trial of the EO-VAE model, and also provides paid use of the EO-VAE. Support call EO-VAE model through api, including Node.js, Python, http.

BiliSakura EO-VAE online free

EO-VAE huggingface.co is an online trial and call api platform, which integrates EO-VAE's modeling effects, including api services, and provides a free online trial of EO-VAE, you can try EO-VAE online for free by clicking the link below.

BiliSakura EO-VAE online free url in huggingface.co:

https://huggingface.co/BiliSakura/EO-VAE

EO-VAE install

EO-VAE is an open source model from GitHub that offers a free installation service, and any user can find EO-VAE on GitHub to install. At the same time, huggingface.co provides the effect of EO-VAE install, users can directly use EO-VAE installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

EO-VAE install url in huggingface.co:

https://huggingface.co/BiliSakura/EO-VAE

Url of EO-VAE

Provider of EO-VAE huggingface.co

BiliSakura
ORGANIZATIONS

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