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@@ -70,6 +70,7 @@ cd UnifiedNeuroGen
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  # Install the required packages
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  pip install -r requirements.txt
 
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  ### Step 2: Download the Model
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@@ -84,6 +85,7 @@ model_path = hf_hub_download(
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  local_dir="./checkpoints" # Download to a local 'checkpoints' folder
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  )
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  print(f"Model downloaded to: {model_path}")
 
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  ### Step 3: Run Inference
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@@ -95,6 +97,7 @@ python sample.py \
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  --ckpt ./checkpoints/unifiedneurogen-eeg2fmri-nat-view-within-subject-demo.pt \
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  --eeg-path /path/to/your/test/eeg/encodings \
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  --save-path /path/to/save/generated/data
 
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  --ckpt: The path to the model checkpoint you downloaded in Step 2.
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@@ -102,7 +105,7 @@ python sample.py \
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  --save-path: The directory where the generated fMRI data will be saved.
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- 📜 Citation
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  If you use this model or the UnifiedNeuroGen framework in your research, please cite the original paper:
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  ```bash
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  @misc{yao2025empoweringfunctionalneuroimagingpretrained,
@@ -113,4 +116,5 @@ If you use this model or the UnifiedNeuroGen framework in your research, please
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  archivePrefix={arXiv},
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  primaryClass={cs.CV},
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  url={[https://arxiv.org/abs/2506.02433](https://arxiv.org/abs/2506.02433)},
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- }
 
 
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  # Install the required packages
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  pip install -r requirements.txt
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+ ```
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  ### Step 2: Download the Model
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  local_dir="./checkpoints" # Download to a local 'checkpoints' folder
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  )
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  print(f"Model downloaded to: {model_path}")
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+ ```
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  ### Step 3: Run Inference
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  --ckpt ./checkpoints/unifiedneurogen-eeg2fmri-nat-view-within-subject-demo.pt \
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  --eeg-path /path/to/your/test/eeg/encodings \
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  --save-path /path/to/save/generated/data
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+ ```
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  --ckpt: The path to the model checkpoint you downloaded in Step 2.
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  --save-path: The directory where the generated fMRI data will be saved.
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+ ## 📜 Citation
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  If you use this model or the UnifiedNeuroGen framework in your research, please cite the original paper:
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  ```bash
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  @misc{yao2025empoweringfunctionalneuroimagingpretrained,
 
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  archivePrefix={arXiv},
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  primaryClass={cs.CV},
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  url={[https://arxiv.org/abs/2506.02433](https://arxiv.org/abs/2506.02433)},
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+ }
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+ ```