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This instruction-only skill is internally consistent with its stated purpose: it generates local PyTorch scaffolds for S2S forecasting and does not request credentials, install software, or call exter... [内容已截断]
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{
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"_id": "k97760x6fwmg10m7z473vhbbp1818fc6",
"changelog": "Major update: The skill now generates full runnable code and training pipelines for S2S AI weather models.\n\n- Renamed from \"s2s-forecasting-expert\" to \"s2s-model-builder\" to reflect code generation capabilities.\n- Provides end-to-end PyTorch code for model architecture, training, inference, and evaluation.\n- Supports FuXi-style, FengWu-style, and AIFS-inspired S2S forecasting models.\n- Implements CRPS loss, probabilistic outputs, distributed training, and ERA5-style data workflows.\n- Maintains strict security: all code runs locally, with no external API calls or data transmissions.",
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"displayName": "Manmeet Singh",
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"displayName": "S2S Forecasting Expert (FuXi, FengWu, AIFS)",
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"slug": "s2s-forecasting-expert",
"stats": {
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"summary": "End-to-end builder for AI-based Subseasonal-to-Seasonal (S2S) forecasting systems. Generates runnable PyTorch code for FuXi-style, FengWu-style, and AIFS-ins...",
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