Download scripts/long_term_forecast/Weather_script/SegRNN.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/long_term_forecast/Weather_script/SegRNN.sh
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hf download hf://lwaekfjlk/Time-Series-Library/scripts/long_term_forecast/Weather_script/SegRNN.sh
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511 Bytes
| export CUDA_VISIBLE_DEVICES=0 | |
| model_name=SegRNN | |
| seq_len=96 | |
| for pred_len in 96 192 336 720 | |
| do | |
| python -u run.py \ | |
| --task_name long_term_forecast \ | |
| --is_training 1 \ | |
| --root_path ./dataset/weather/ \ | |
| --data_path weather.csv \ | |
| --model_id weather_$seq_len'_'$pred_len \ | |
| --model $model_name \ | |
| --data custom \ | |
| --features M \ | |
| --seq_len $seq_len \ | |
| --pred_len $pred_len \ | |
| --seg_len 48 \ | |
| --enc_in 21 \ | |
| --d_model 512 \ | |
| --dropout 0.5 \ | |
| --learning_rate 0.0001 \ | |
| --des 'Exp' \ | |
| --itr 1 | |
| done | |