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vroom-sbi
arpan-52/vroom-sbi
vroom-sbi is a machine learning model from arpan-52. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Trained neural posterior estimators for Rotation Measure (RM) synthesis.
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Public
Updated May 15, 2026
Repo size
441 MB
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.pt357 MB · 100%
At a glance
- License
- mit
- Access
- Public
- Created
- Dec 11, 2025
- Updated
- May 15, 2026
- SHA
- 647989a3
Model card
From the Hugging Face model README
VROOM-SBI Trained Models
Trained neural posterior estimators for Rotation Measure (RM) synthesis.
Model Information
- Model Types: burn, external, faraday, internal
- Max Components: 1
- Classifier: No
- Upload Date: 2026-02-17
Files
| File | Description |
|---|---|
| posterior_burn_slab_n1.pt | Posterior model (.pt) |
| posterior_external_dispersion_n1.pt | Posterior model (.pt) |
| posterior_faraday_thin_n1.pt | Posterior model (.pt) |
| posterior_internal_dispersion_n1.pt | Posterior model (.pt) |
| training_burn_slab_n1.png | Training plot |
| training_external_dispersion_n1.png | Training plot |
| training_faraday_thin_n1.png | Training plot |
| training_internal_dispersion_n1.png | Training plot |
| training_summary.txt | Summary file |
Usage
from vroom_sbi.inference import InferenceEngine
# Load models
engine = InferenceEngine(model_dir="path/to/downloaded/models")
engine.load_models()
# Run inference
result, all_results = engine.infer(qu_obs)
print(f"Best model: {result.n_components} components")
Citation
If you use these models, please cite:
[Citation information to be added]
- License
- mit
- Created
- Dec 11, 2025
- Updated
- May 15, 2026