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solafune-precipitation-nowcasting
camaro/solafune-precipitation-nowcasting
solafune-precipitation-nowcasting is a machine learning model from camaro. 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.
The 11 model checkpoints behind the final submission (equal-weight blend, Public LB 0.6360204).
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Public
Updated Aug 8, 2026
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2.9 GB
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.pt2.9 GB · 100%
At a glance
- License
- mit
- Access
- Public
- Created
- Aug 8, 2026
- Updated
- Aug 8, 2026
- SHA
- 0673d40f
Model card
From the Hugging Face model README
Solafune Precipitation Nowcasting — final submission weights
The 11 model checkpoints behind the final submission (equal-weight blend, Public LB 0.6360204).
Each file is the EMA state_dict at epoch 10 of a model trained on all 20 training locations.
No optimizer, scheduler or RNG state is included.
| file | temporal fusion | stem stride | frames | extras | seed | TTA |
|---|---|---|---|---|---|---|
| exp175/model_best.pt | stack2d | 1 | 3 | — | 42 | 8 |
| exp176/model_best.pt | conv3d | 2 | 3 | spectral adapter | 42 | 8 |
| exp177/model_best.pt | stack2d | 2 | 3 | — | 1234 | 8 |
| exp178/model_best.pt | stack2d | 1 | 3 | multiscale skip | 42 | 8 |
| exp179/model_best.pt | stack2d | 2 | 3 | satellite FiLM | 42 | 8 |
| exp180/model_best.pt | conv3d | 4 | 3 | spectral adapter, rot360 aug | 42 | 3 |
| exp182/model_best.pt | stack2d | 1 | 3 | — | 1234 | 8 |
| exp183/model_best.pt | conv3d | 2 | 3 | spectral adapter | 1234 | 8 |
| exp184/model_best.pt | stack2d | 2 | 3 | satellite FiLM | 1234 | 8 |
| exp185/model_best.pt | stack2d | 1 | 3 | multiscale skip | 1234 | 8 |
| exp186/model_best.pt | conv3d | 2 | 6 | multiscale skip, target alignment, IR temporal stats | 42 | 8 |
Usage
The checkpoints only load against the matching model definition. Place them under
src/output/expNNN/model_best.pt in the solution repository, then run stages 2 and 3 of src/run.sh.
from configs import load_config
from data import data_input_channels, data_input_frames
from model import NowcastModel
import torch
cfg = load_config("configs/exp175.py")
model = NowcastModel(cfg.model, cfg.data.target_size,
data_input_channels(cfg.data), data_input_frames(cfg.data))
model.load_state_dict(torch.load("output/exp175/model_best.pt", map_location="cpu", weights_only=True))
- License
- mit
- Created
- Aug 8, 2026
- Updated
- Aug 8, 2026