Other
Transformers
Safetensors
weathernext2
weather
forecasting
climate
tropical-cyclones
graph-neural-network
Instructions to use kashif/weathernext2-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kashif/weathernext2-mini with Transformers:
# Load model directly from transformers import WeatherNext2ForWeatherForecasting model = WeatherNext2ForWeatherForecasting.from_pretrained("kashif/weathernext2-mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "aggregate_normalization": null, | |
| "architectures": [ | |
| "WeatherNext2ForWeatherForecasting" | |
| ], | |
| "atmospheric_variables": [ | |
| "temperature", | |
| "geopotential", | |
| "u_component_of_wind", | |
| "v_component_of_wind", | |
| "vertical_velocity", | |
| "specific_humidity" | |
| ], | |
| "attention_dropout": 0.0, | |
| "attention_k_hop": 16, | |
| "ball_query_radius_fraction": 0.6, | |
| "dtype": "float32", | |
| "edge_hidden_size": 32, | |
| "forcing_variables": [ | |
| "year_progress_sin", | |
| "year_progress_cos", | |
| "day_progress_sin", | |
| "day_progress_cos" | |
| ], | |
| "global_variables": [ | |
| "year_progress_sin", | |
| "year_progress_cos" | |
| ], | |
| "grid_latitudes": 181, | |
| "grid_longitudes": 360, | |
| "hidden_act": "gelu_pytorch_tanh", | |
| "hidden_size": 512, | |
| "initializer_range": 0.02, | |
| "input_variables": [ | |
| "temperature", | |
| "geopotential", | |
| "u_component_of_wind", | |
| "v_component_of_wind", | |
| "vertical_velocity", | |
| "specific_humidity", | |
| "2m_temperature", | |
| "mean_sea_level_pressure", | |
| "10m_v_component_of_wind", | |
| "10m_u_component_of_wind", | |
| "sea_surface_temperature", | |
| "geopotential_at_surface", | |
| "land_sea_mask", | |
| "year_progress_sin", | |
| "year_progress_cos", | |
| "day_progress_sin", | |
| "day_progress_cos" | |
| ], | |
| "intermediate_size": 2048, | |
| "layer_norm_eps": 1e-05, | |
| "mesh_splits": 5, | |
| "mlp_act": "silu", | |
| "model_type": "weathernext2", | |
| "noise_channels": 32, | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 16, | |
| "num_input_timesteps": 2, | |
| "pressure_levels": [ | |
| 50, | |
| 100, | |
| 150, | |
| 200, | |
| 250, | |
| 300, | |
| 400, | |
| 500, | |
| 600, | |
| 700, | |
| 850, | |
| 925, | |
| 1000 | |
| ], | |
| "sigmoid_shifted_outputs": { | |
| "cyclone_exists_gaussian_unit_mode": 2.0 | |
| }, | |
| "static_variables": [ | |
| "geopotential_at_surface", | |
| "land_sea_mask" | |
| ], | |
| "target_variables": [ | |
| "temperature", | |
| "geopotential", | |
| "u_component_of_wind", | |
| "v_component_of_wind", | |
| "vertical_velocity", | |
| "specific_humidity", | |
| "2m_temperature", | |
| "mean_sea_level_pressure", | |
| "10m_v_component_of_wind", | |
| "10m_u_component_of_wind", | |
| "sea_surface_temperature", | |
| "total_precipitation_6hr", | |
| "cyclone_exists_gaussian_unit_mode", | |
| "cyclone_all_wind_disc", | |
| "cyclone_usa_wind_disc", | |
| "cyclone_usa_r34_ne_radius_disc", | |
| "cyclone_usa_r34_se_radius_disc", | |
| "cyclone_usa_r34_sw_radius_disc", | |
| "cyclone_usa_r34_nw_radius_disc", | |
| "cyclone_usa_r50_ne_radius_disc", | |
| "cyclone_usa_r50_se_radius_disc", | |
| "cyclone_usa_r50_sw_radius_disc", | |
| "cyclone_usa_r50_nw_radius_disc", | |
| "cyclone_usa_r64_ne_radius_disc", | |
| "cyclone_usa_r64_se_radius_disc", | |
| "cyclone_usa_r64_sw_radius_disc", | |
| "cyclone_usa_r64_nw_radius_disc", | |
| "cyclone_usa_rmw_disc", | |
| "cyclone_usa_pres_disc" | |
| ], | |
| "time_step_hours": 6, | |
| "transformers_version": "5.15.0.dev0" | |
| } | |