Implementation of:
This repository contains the code for the SiMBA (Simplified Mamba-based Architecture for Vision and Multivariate Time series), a transformer-based model that can process both visual and time series inputs.
To install the required dependencies, run the following command:
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To train the model, run the following command:
python train.py --config config.json
where config.json is the path to the configuration file.
To evaluate the trained model, run the following command:
python evaluate.py --model_path best_model.pth --data_path data/test.json
where best_model.pth is the path to the trained model and data/test.json is the path to the test data.
The configuration file is a JSON file that specifies the hyperparameters for the model. The following options are available:
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This code is licensed under the MIT License.