Instructions to use hf-internal-testing/tiny-random-WeatherNext2ForWeatherForecasting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-WeatherNext2ForWeatherForecasting with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import WeatherNext2ForWeatherForecasting model = WeatherNext2ForWeatherForecasting.from_pretrained("hf-internal-testing/tiny-random-WeatherNext2ForWeatherForecasting", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Move mask
Browse filesKeep the mesh mask with preprocessing. Tensor values are unchanged; checked checkpoint roundtrips and local forecasts.
- attention_mask.safetensors +3 -0
- model.safetensors +2 -2
- preprocessor_config.json +3 -339
attention_mask.safetensors
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model.safetensors
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size 117444
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preprocessor_config.json
CHANGED
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| 123 |
"feature_extractor_type": "WeatherNext2FeatureExtractor",
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| 124 |
"forcing_variables": [
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| 125 |
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|
@@ -152,119 +40,7 @@
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| 152 |
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"pressure_levels": [
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@@ -275,119 +51,7 @@
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| 392 |
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| 393 |
"geopotential",
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| 7 |
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| 11 |
"feature_extractor_type": "WeatherNext2FeatureExtractor",
|
| 12 |
"forcing_variables": [
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| 13 |
"year_progress_sin",
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| 40 |
"day_progress_sin",
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| 41 |
"day_progress_cos"
|
| 42 |
],
|
| 43 |
+
"mean_by_level": {},
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| 44 |
"nan_fill_values": {},
|
| 45 |
"num_input_timesteps": 2,
|
| 46 |
"pressure_levels": [
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|
| 51 |
"geopotential_at_surface",
|
| 52 |
"land_sea_mask"
|
| 53 |
],
|
| 54 |
+
"stddev_by_level": {},
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| 55 |
"target_variables": [
|
| 56 |
"temperature",
|
| 57 |
"geopotential",
|