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# EEG-to-Text RawNet Model
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Brain-Computer Interface model for translating EEG signals to text.
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## Model Details
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- Architecture: RawNet (Multi-scale Conv1D + Transformer)
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- Best Validation Loss: 0.6647
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- Parameters: 33,956,593
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## Usage
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```python
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from huggingface_hub import hf_hub_download
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import torch
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model_path = hf_hub_download(repo_id="sajjad5221/eeg2text", filename="best_rawnet_model.pt")
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checkpoint = torch.load(model_path)
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model.load_state_dict(checkpoint['model_state_dict'])
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```
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Dataset: [sajjad5221/eeg2text-emmt-dataset](https://huggingface.co/datasets/sajjad5221/eeg2text-emmt-dataset)
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# EEG-to-Text RawNet Model
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Brain-Computer Interface model for translating EEG signals to text(on EMMT dataset).
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Dataset: [sajjad5221/eeg2text-emmt-dataset](https://huggingface.co/datasets/sajjad5221/eeg2text-emmt-dataset)
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