{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.11.11","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":87793,"databundleVersionId":12255112,"sourceType":"competition"},{"sourceId":11783297,"sourceType":"datasetVersion","datasetId":7398046}],"dockerImageVersionId":31012,"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# Copy all files from your uploaded dataset into the working directory\n!cp -r /kaggle/input/rna-submission-bundle/kaggle/* /kaggle/working/\n%cd /kaggle/working/\n\n# Run inference using the provided test_sequences.csv from the competition\n!python inference.py \\\n  --sequences /kaggle/input/stanford-rna-3d-folding/test_sequences.csv \\\n  --weights checkpoints/best_train_model.pt \\\n  --output submission.csv \\\n  --idcol target_id\n","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2025-05-12T13:39:17.390117Z","iopub.execute_input":"2025-05-12T13:39:17.390401Z","iopub.status.idle":"2025-05-12T13:39:22.539072Z","shell.execute_reply.started":"2025-05-12T13:39:17.390378Z","shell.execute_reply":"2025-05-12T13:39:22.538199Z"}},"outputs":[],"execution_count":null}]}