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README.md

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+---
+license: apache-2.0
+library_name: pytorch
+tags:
+  - weather
+  - era5
+  - pytorch
+  - sonny
+pipeline_tag: other
+---
+
+# Sonny — 69-channel ERA5-like backbone (120×240, 6 h)
+
+**Sonny** is a ViT-style one-step weather backbone trained at 1.5°-style resolution (lat×lon = 120×240), 69 ERA5-like variables, patch size 2, EMA weights at epoch 50.
+
+## Loading (with the `stormer` codebase)
+
+This Hub snapshot stores weights only (`model.safetensors`) plus `config.json` (`init_args`). You need the same Python dependencies as training (**PyTorch**, **timm**, **xformers** on GPU, etc.) and the `stormer` package that defines the model.
+
+```python
+from stormer.models.hub.sonny import load_sonny_from_hub
+
+model = load_sonny_from_hub("Francismj/sonny-era5-backbone", map_location="cuda")
+model.eval()
+```
+
+Or download files manually and build :class:`~stormer.models.hub.sonny.Sonny`(**init_args**) then :meth:`load_state_dict`.
+
+## Files
+
+- `config.json` — hyperparameters / variable list for :class:`Sonny`
+- `model.safetensors` — EMA ``ema_model_state_dict``
+- `normalization_note.txt` — reminder to use your local ``normalization_constants`` from the training repo for real inference
+
+## Citation
+
+If you use this checkpoint, cite your project / paper and link this model card.

config.json

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+{
+  "sonny_version": "1.0",
+  "architecture_name": "sonny",
+  "class_qualname": "stormer.models.hub.sonny.Sonny",
+  "source_checkpoint": "stormbreaker5_checkpoint_ema_epoch_050.pth",
+  "source_epoch": 50,
+  "init_args": {
+    "variables": [
+      "2m_temperature",
+      "10m_u_component_of_wind",
+      "10m_v_component_of_wind",
+      "mean_sea_level_pressure",
+      "geopotential_50",
+      "geopotential_100",
+      "geopotential_150",
+      "geopotential_200",
+      "geopotential_250",
+      "geopotential_300",
+      "geopotential_400",
+      "geopotential_500",
+      "geopotential_600",
+      "geopotential_700",
+      "geopotential_850",
+      "geopotential_925",
+      "geopotential_1000",
+      "u_component_of_wind_50",
+      "u_component_of_wind_100",
+      "u_component_of_wind_150",
+      "u_component_of_wind_200",
+      "u_component_of_wind_250",
+      "u_component_of_wind_300",
+      "u_component_of_wind_400",
+      "u_component_of_wind_500",
+      "u_component_of_wind_600",
+      "u_component_of_wind_700",
+      "u_component_of_wind_850",
+      "u_component_of_wind_925",
+      "u_component_of_wind_1000",
+      "v_component_of_wind_50",
+      "v_component_of_wind_100",
+      "v_component_of_wind_150",
+      "v_component_of_wind_200",
+      "v_component_of_wind_250",
+      "v_component_of_wind_300",
+      "v_component_of_wind_400",
+      "v_component_of_wind_500",
+      "v_component_of_wind_600",
+      "v_component_of_wind_700",
+      "v_component_of_wind_850",
+      "v_component_of_wind_925",
+      "v_component_of_wind_1000",
+      "temperature_50",
+      "temperature_100",
+      "temperature_150",
+      "temperature_200",
+      "temperature_250",
+      "temperature_300",
+      "temperature_400",
+      "temperature_500",
+      "temperature_600",
+      "temperature_700",
+      "temperature_850",
+      "temperature_925",
+      "temperature_1000",
+      "specific_humidity_50",
+      "specific_humidity_100",
+      "specific_humidity_150",
+      "specific_humidity_200",
+      "specific_humidity_250",
+      "specific_humidity_300",
+      "specific_humidity_400",
+      "specific_humidity_500",
+      "specific_humidity_600",
+      "specific_humidity_700",
+      "specific_humidity_850",
+      "specific_humidity_925",
+      "specific_humidity_1000"
+    ],
+    "in_img_size": [
+      120,
+      240
+    ],
+    "patch_size": 2,
+    "use_cnn_head": true,
+    "cnn_head_channels": 256,
+    "hidden_size": 384,
+    "depth": 12,
+    "num_heads": 6,
+    "mlp_ratio": 4.0,
+    "step_ratio": 0.5
+  }
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4d9c715bb4ac0c29589dde4f66f3a4e8706958feb04ec6d5912bd413af144f7b
+size 94337712

normalization_note.txt

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+For evaluation/inference you still need normalize_mean.npz / normalize_std.npz / normalize_diff_std_*.npz from the training repository (normalization_constants/).