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# Hweh-6M
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Hweh-6M is a **6 million parameter LSTM** trained to predict the next **12 hours of weather**, including temperature, humidity, pressure, precipitation, and more, using the previous **72 hours of weather context**.
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We recommend using this model as a backup to a weather API or for offline forecasting if internet access is unavailable.
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---
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# Hweh-6M
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**Hweh-6M** is a **6-million-parameter LSTM model** trained to predict the next **12 hours of weather**, including temperature, humidity, pressure, precipitation, and more, using the previous **72 hours of weather context**.
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We recommend using this model as a backup to a weather API or for offline forecasting when internet access is unavailable.
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This model was primarily trained to serve as a teacher for [Hweh-446k](https://huggingface.co/Harley-ml/Hweh-446k).
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We would also like to give a shoutout to [**Open-Meteo**](https://open-meteo.com/) for providing a **free-to-use weather forecasting API**.
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## Architecture
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The model uses a multitask LSTM setup:
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| Parameter | Value |
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| ----------------------- | ---------------------------------------------- |
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| `input_dim` | `22` |
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| `seq_len` | `72` |
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| `num_predict` | `12` |
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| `hidden_dim` | `384` |
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| `num_layers` | `6` |
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| `dropout` | `0.1` |
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| `encoder_type` | `lstm` |
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| `num_locations` | `82` |
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| `location_emb_dim` | `32` |
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| `num_weather_classes` | `7` |
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