Download scripts/anomaly_detection/SWAT/Autoformer.sh from lwaekfjlk/Time-Series-Library: direct link, hf CLI and curl.
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https://huggingface.co/lwaekfjlk/Time-Series-Library/resolve/main/scripts/anomaly_detection/SWAT/Autoformer.sh
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hf download hf://lwaekfjlk/Time-Series-Library/scripts/anomaly_detection/SWAT/Autoformer.sh
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curl -L -o Autoformer.sh https://huggingface.co/lwaekfjlk/Time-Series-Library/resolve/main/scripts/anomaly_detection/SWAT/Autoformer.sh
402 Bytes
| export CUDA_VISIBLE_DEVICES=1 | |
| python -u run.py \ | |
| --task_name anomaly_detection \ | |
| --is_training 1 \ | |
| --root_path ./dataset/SWaT \ | |
| --model_id SWAT \ | |
| --model Autoformer \ | |
| --data SWAT \ | |
| --features M \ | |
| --seq_len 100 \ | |
| --pred_len 0 \ | |
| --d_model 128 \ | |
| --d_ff 128 \ | |
| --e_layers 3 \ | |
| --enc_in 51 \ | |
| --c_out 51 \ | |
| --top_k 3 \ | |
| --anomaly_ratio 1 \ | |
| --batch_size 128 \ | |
| --train_epochs 3 |