Time Series Forecasting
Joblib
Keras
PyTorch
generic
demand-forecasting
supply-chain
gru
lstm
lightgbm
xgboost
random-forest
mixture-of-experts
Instructions to use AbdullahImran/Saudi-Supply-Demand-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use AbdullahImran/Saudi-Supply-Demand-Models with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://AbdullahImran/Saudi-Supply-Demand-Models") - Notebooks
- Google Colab
- Kaggle
Add dl_multi_horizon_rewrite_out
Browse files- dl_multi_horizon_rewrite_out/best_model.pth +3 -0
- dl_multi_horizon_rewrite_out/dl_results.json +86 -0
- dl_multi_horizon_rewrite_out/feature_cols.joblib +3 -0
- dl_multi_horizon_rewrite_out/final_model.pth +3 -0
- dl_multi_horizon_rewrite_out/label_encoder.joblib +3 -0
- dl_multi_horizon_rewrite_out/scaler.joblib +3 -0
- dl_multi_horizon_rewrite_out/training_history.json +1 -0
dl_multi_horizon_rewrite_out/best_model.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:14c82246e60270dfd07c4338777deaf91c8b8a3aa1ef0da26b8147e1261ab7f6
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size 196533
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dl_multi_horizon_rewrite_out/dl_results.json
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{
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"per_h_test": [
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[
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],
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"per_item_rmse_summary": {
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"count": 300.0,
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"mean": 0.25592849414758445,
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"std": 0.23498478884444102,
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"min": 0.042720060106310215,
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"25%": 0.11809405403173874,
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"max": 2.1635145464541035
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}
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}
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dl_multi_horizon_rewrite_out/feature_cols.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:3aef3269f630e72c0c27d51bb858e01d73a9fd24a41aa52a220a7a6bc5a58a38
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size 118
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dl_multi_horizon_rewrite_out/final_model.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:035ce75716f3047870b7d87cc80c2532d31f44d40991e5f473adefb5cad2c9c6
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size 196556
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dl_multi_horizon_rewrite_out/label_encoder.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:44b9e05b06a5fe58ca782a3452babb9b7418bad5041bc63f563df511506264ca
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size 4935
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dl_multi_horizon_rewrite_out/scaler.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:663dddf979dd3fc3e98df2373759579addd157e3159d4ec490fb580b2baf055c
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size 855
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dl_multi_horizon_rewrite_out/training_history.json
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{"train_loss": [0.420379136571821, 0.3209524110255652, 0.301205068629309, 0.29412394273557413, 0.2893803423110223, 0.2833350258848525, 0.28190813975914425, 0.27659013250608316, 0.2718466754188601, 0.2711587144148271, 0.26884723657014353, 0.26478204496254193, 0.2645204507850653, 0.26051855222969655, 0.26167739338136664, 0.2585892395073215, 0.2543265478352442, 0.2520169062872991, 0.2483490343322817, 0.2499433769443572, 0.24772298089321085], "val_loss": [0.2621903195977211, 0.22298920564353467, 0.23979015313088894, 0.2171830404549837, 0.20785962585359813, 0.19959951490163802, 0.20484395660459995, 0.1963156022131443, 0.19636834897100924, 0.21296003088355064, 0.18555684871971606, 0.2032909445464611, 0.20500157102942468, 0.20245156437158585, 0.22487947680056095, 0.20367187522351743, 0.20915884524583817, 0.20575357060879468, 0.20994049161672593, 0.19820770490914583, 0.20810474455356598]}
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