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.gitattributes

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README.md

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+---
+license: mit
+tags:
+- time-series-forecasting
+- financial-data
+- neural-networks
+- lstm
+- transformer
+- tensorflow
+library_name: tensorflow
+---
+
+# FinTech Neural Forecasters
+
+This repository contains neural network models for financial time series forecasting, part of the FinTech DataGen project.
+
+## Models Included
+
+### LSTM Forecaster
+- **Algorithm**: Long Short-Term Memory Neural Network
+- **Architecture**: Single LSTM layer with Dense output
+- **Lookback**: 10 time steps
+- **Performance**: RMSE=1.89, MAE=1.45, MAPE=1.42%
+
+### Transformer Forecaster
+- **Algorithm**: Transformer with multi-head attention
+- **Architecture**: d_model=32, num_heads=2, ff_dim=64
+- **Lookback**: 10 time steps
+- **Performance**: RMSE=1.76, MAE=1.38, MAPE=1.35%
+
+## Usage
+
+```python
+import tensorflow as tf
+from huggingface_hub import snapshot_download, hf_hub_download
+import joblib
+
+# Method 1: Download complete forecaster objects (Recommended)
+lstm_forecaster_path = hf_hub_download(repo_id="abdullah-daoud/fintech-neural-forecasters", filename="lstm_forecaster.pkl")
+transformer_forecaster_path = hf_hub_download(repo_id="abdullah-daoud/fintech-neural-forecasters", filename="transformer_forecaster.pkl")
+
+# Load complete forecasters
+lstm_forecaster = joblib.load(lstm_forecaster_path)
+transformer_forecaster = joblib.load(transformer_forecaster_path)
+
+# Make predictions
+lstm_predictions = lstm_forecaster.predict(steps=5)
+transformer_predictions = transformer_forecaster.predict(steps=5)
+
+# Method 2: Download individual model files
+repo_path = snapshot_download(repo_id="abdullah-daoud/fintech-neural-forecasters")
+
+# Load individual TensorFlow models
+lstm_model = tf.keras.models.load_model(f"{repo_path}/lstm_model")
+transformer_model = tf.keras.models.load_model(f"{repo_path}/transformer_model")
+
+# Load scalers if available
+try:
+    lstm_scaler = joblib.load(f"{repo_path}/lstm_model/scaler.pkl")
+    transformer_scaler = joblib.load(f"{repo_path}/transformer_model/scaler.pkl")
+except FileNotFoundError:
+    print("Scalers not found - models may handle scaling internally")
+```
+
+## Requirements
+- tensorflow>=2.13.0
+- numpy>=1.24.3
+- pandas>=2.0.3
+- scikit-learn>=1.3.0
+
+## Citation
+```
+@software{fintech_datagen_2025,
+  title={FinTech DataGen: Complete Financial Forecasting Application},
+  author={FinTech DataGen Team},
+  year={2025},
+  url={https://github.com/your_username/fintech-datagen}
+}
+```

config.json

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+{
+  "model_type": "neural_forecasters",
+  "models": [
+    "lstm",
+    "transformer"
+  ],
+  "framework": "tensorflow",
+  "task": "time-series-forecasting",
+  "dataset": "financial_ohlcv",
+  "metrics": {
+    "lstm": {
+      "rmse": 1.89,
+      "mae": 1.45,
+      "mape": 1.42
+    },
+    "transformer": {
+      "rmse": 1.76,
+      "mae": 1.38,
+      "mape": 1.35
+    }
+  }
+}

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