| --- |
| license: cc-by-4.0 |
| pipeline_tag: feature-extraction |
| tags: |
| - seismology |
| - site-effects |
| - generative-model |
| - flow-matching |
| - Vs30 |
| - HVSR |
| --- |
| |
| # JsT V4 — Just seismic Transformer |
|
|
| An 8-token conditional flow-matching generative model for three-component |
| P-wave seismograms. Turns one earthquake record into a site-effect measurement. |
|
|
| ## Model |
|
|
| - **Architecture**: 8-token condition encoder (source×3, path×4, receiver×1) + |
| 8-layer flow-matching transformer (512 dim, 8 heads), adaLN-Zero modulation, |
| 1-D rotary position encoding |
| - **Params**: 5.3M (encoder) + transformer denoiser |
| - **Training**: 800 epochs, batch 1024, AdamW, cosine annealing |
| - **Data**: MLAAPDE v2.1 36-month P-wave cache (56,047 source–station pairs) |
| - **Inference**: 50-step Heun ODE integration, CFG scale 1.0 |
|
|
| ## Usage |
|
|
| ```python |
| import torch |
| from JsT import load_checkpoint_models, AblationConditionEncoder |
| |
| device = torch.device("cuda") |
| ce, dn, ckpt = load_checkpoint_models( |
| "checkpoint-last.pth", device, use_ema=True, |
| sampling_method="heun", steps=50, cfg_scale=1.0, |
| ) |
| ce = AblationConditionEncoder(ce, [8, 9, 10]) # remove identity tokens |
| dn.eval(); ce.eval() |
| ``` |
|
|
| Full code: [Just-seismic-Transformer](https://github.com/grayguy2002/Just-seismic-Transformer) |
|
|
| ## Reference |
|
|
| Preprint forthcoming. When using this checkpoint, please cite the corresponding |
| paper and the JsT code repository. |
|
|
| ## License |
|
|
| This checkpoint is released under **CC BY 4.0**. |
| The accompanying code is released under **MIT**. |
|
|
