Restore per-config dataset_info and configs in dataset card

README.md

@@ -10,8 +10,3881 @@ tags:
 pretty_name: GiftEval Pretrain (Derived)
 size_categories:
   - 100K<n<1M
+dataset_info:
+- config_name: BEIJING_SUBWAY_30MIN
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 5278431
+    num_examples: 276
+  download_size: 1817091
+  dataset_size: 5278431
+- config_name: HZMETRO
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 506200
+    num_examples: 80
+  download_size: 464658
+  dataset_size: 506200
+- config_name: LOS_LOOP
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 9936684
+    num_examples: 207
+  download_size: 9934935
+  dataset_size: 9936684
+- config_name: PEMS03
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 12920623
+    num_examples: 358
+  download_size: 12557169
+  dataset_size: 12920623
+- config_name: PEMS04
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 25294289
+    num_examples: 307
+  download_size: 23837711
+  dataset_size: 25294289
+- config_name: PEMS07
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 34158754
+    num_examples: 883
+  download_size: 31232731
+  dataset_size: 34158754
+- config_name: PEMS08
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 14834859
+    num_examples: 170
+  download_size: 13143003
+  dataset_size: 14834859
+- config_name: PEMS_BAY
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 21091643
+    num_examples: 325
+  download_size: 20684874
+  dataset_size: 21091643
+- config_name: Q-TRAFFIC
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 1065920457
+    num_examples: 45148
+  download_size: 1063325088
+  dataset_size: 1065920457
+- config_name: SHMETRO
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 7120545
+    num_examples: 288
+  download_size: 6364755
+  dataset_size: 7120545
+- config_name: alibaba_cluster_trace_2018
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 585186938
+    num_examples: 58409
+  download_size: 525625284
+  dataset_size: 585186938
+- config_name: australian_electricity_demand
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 5672823
+    num_examples: 5
+  download_size: 5676574
+  dataset_size: 5672823
+- config_name: azure_vm_traces_2017
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 10768952310
+    num_examples: 159472
+  download_size: 10758544077
+  dataset_size: 10768952310
+- config_name: bdg-2_bear
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 5766465
+    num_examples: 91
+  download_size: 5064490
+  dataset_size: 5766465
+- config_name: bdg-2_fox
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
+      list: float32
+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 5351024
+    num_examples: 135
+  download_size: 5352053
+  dataset_size: 5351024
+- config_name: bdg-2_panther
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
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+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
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+    num_examples: 105
+  download_size: 2304486
+  dataset_size: 2321093
+- config_name: bdg-2_rat
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
+    list:
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+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
+    num_bytes: 11238253
+    num_examples: 280
+  download_size: 11163044
+  dataset_size: 11238253
+- config_name: beijing_air_quality
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
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+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
+  - name: train
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+    num_examples: 12
+  download_size: 6532110
+  dataset_size: 6756198
+- config_name: bitcoin_with_missing
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
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+  - name: past_feat_dynamic_real
+    list:
+      list: float32
+  splits:
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+    num_examples: 18
+  download_size: 360587
+  dataset_size: 360759
+- config_name: borealis
+  features:
+  - name: dataset_name
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+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
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+  - name: past_feat_dynamic_real
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+    num_examples: 15
+  download_size: 511722
+  dataset_size: 508432
+- config_name: borg_cluster_data_2011
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
+  - name: freq
+    dtype: string
+  - name: target
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+  - name: past_feat_dynamic_real
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+      list: float32
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+  dataset_size: 3719472276
+- config_name: buildings_900k
+  features:
+  - name: dataset_name
+    dtype: string
+  - name: item_id
+    dtype: string
+  - name: start
+    dtype: timestamp[s]
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+  download_size: 61062732368
+  dataset_size: 63367685876
+- config_name: bull
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+  - name: start
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+- config_name: cdc_fluview_ilinet
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+  - name: item_id
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+  dataset_size: 1050827
+- config_name: cdc_fluview_who_nrevss
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+- config_name: china_air_quality
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+- config_name: cif_2016_12
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+- config_name: cif_2016_6
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+- config_name: australian_electricity_demand
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+- config_name: covid_mobility
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+- config_name: elecdemand
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+    path: elecdemand/train-*
+- config_name: elf
+  data_files:
+  - split: train
+    path: elf/train-*
+- config_name: era5_1989
+  data_files:
+  - split: train
+    path: era5_1989/train-*
+- config_name: era5_1990
+  data_files:
+  - split: train
+    path: era5_1990/train-*
+- config_name: era5_1991
+  data_files:
+  - split: train
+    path: era5_1991/train-*
+- config_name: era5_1992
+  data_files:
+  - split: train
+    path: era5_1992/train-*
+- config_name: era5_1993
+  data_files:
+  - split: train
+    path: era5_1993/train-*
+- config_name: era5_1994
+  data_files:
+  - split: train
+    path: era5_1994/train-*
+- config_name: era5_1995
+  data_files:
+  - split: train
+    path: era5_1995/train-*
+- config_name: era5_1996
+  data_files:
+  - split: train
+    path: era5_1996/train-*
+- config_name: era5_1997
+  data_files:
+  - split: train
+    path: era5_1997/train-*
+- config_name: era5_1998
+  data_files:
+  - split: train
+    path: era5_1998/train-*
+- config_name: era5_1999
+  data_files:
+  - split: train
+    path: era5_1999/train-*
+- config_name: era5_2000
+  data_files:
+  - split: train
+    path: era5_2000/train-*
+- config_name: era5_2001
+  data_files:
+  - split: train
+    path: era5_2001/train-*
+- config_name: era5_2002
+  data_files:
+  - split: train
+    path: era5_2002/train-*
+- config_name: era5_2003
+  data_files:
+  - split: train
+    path: era5_2003/train-*
+- config_name: era5_2004
+  data_files:
+  - split: train
+    path: era5_2004/train-*
+- config_name: era5_2005
+  data_files:
+  - split: train
+    path: era5_2005/train-*
+- config_name: era5_2006
+  data_files:
+  - split: train
+    path: era5_2006/train-*
+- config_name: era5_2007
+  data_files:
+  - split: train
+    path: era5_2007/train-*
+- config_name: era5_2008
+  data_files:
+  - split: train
+    path: era5_2008/train-*
+- config_name: era5_2009
+  data_files:
+  - split: train
+    path: era5_2009/train-*
+- config_name: era5_2010
+  data_files:
+  - split: train
+    path: era5_2010/train-*
+- config_name: era5_2011
+  data_files:
+  - split: train
+    path: era5_2011/train-*
+- config_name: era5_2012
+  data_files:
+  - split: train
+    path: era5_2012/train-*
+- config_name: era5_2013
+  data_files:
+  - split: train
+    path: era5_2013/train-*
+- config_name: era5_2014
+  data_files:
+  - split: train
+    path: era5_2014/train-*
+- config_name: era5_2015
+  data_files:
+  - split: train
+    path: era5_2015/train-*
+- config_name: era5_2016
+  data_files:
+  - split: train
+    path: era5_2016/train-*
+- config_name: era5_2017
+  data_files:
+  - split: train
+    path: era5_2017/train-*
+- config_name: era5_2018
+  data_files:
+  - split: train
+    path: era5_2018/train-*
+- config_name: extended_web_traffic_with_missing
+  data_files:
+  - split: train
+    path: extended_web_traffic_with_missing/train-*
+- config_name: favorita_sales
+  data_files:
+  - split: train
+    path: favorita_sales/train-*
+- config_name: favorita_transactions
+  data_files:
+  - split: train
+    path: favorita_transactions/train-*
+- config_name: fred_md
+  data_files:
+  - split: train
+    path: fred_md/train-*
+- config_name: gfc14_load
+  data_files:
+  - split: train
+    path: gfc14_load/train-*
+- config_name: godaddy
+  data_files:
+  - split: train
+    path: godaddy/train-*
+- config_name: hog
+  data_files:
+  - split: train
+    path: hog/train-*
+- config_name: ideal
+  data_files:
+  - split: train
+    path: ideal/train-*
+- config_name: kaggle_web_traffic_weekly
+  data_files:
+  - split: train
+    path: kaggle_web_traffic_weekly/train-*
+- config_name: kdd2022
+  data_files:
+  - split: train
+    path: kdd2022/train-*
+- config_name: largest_2017
+  data_files:
+  - split: train
+    path: largest_2017/train-*
+- config_name: largest_2018
+  data_files:
+  - split: train
+    path: largest_2018/train-*
+- config_name: largest_2019
+  data_files:
+  - split: train
+    path: largest_2019/train-*
+- config_name: largest_2020
+  data_files:
+  - split: train
+    path: largest_2020/train-*
+- config_name: largest_2021
+  data_files:
+  - split: train
+    path: largest_2021/train-*
+- config_name: lcl
+  data_files:
+  - split: train
+    path: lcl/train-*
+- config_name: london_smart_meters_with_missing
+  data_files:
+  - split: train
+    path: london_smart_meters_with_missing/train-*
+- config_name: m1_monthly
+  data_files:
+  - split: train
+    path: m1_monthly/train-*
+- config_name: m1_quarterly
+  data_files:
+  - split: train
+    path: m1_quarterly/train-*
+- config_name: m1_yearly
+  data_files:
+  - split: train
+    path: m1_yearly/train-*
+- config_name: m5
+  data_files:
+  - split: train
+    path: m5/train-*
+- config_name: monash_m3_monthly
+  data_files:
+  - split: train
+    path: monash_m3_monthly/train-*
+- config_name: monash_m3_other
+  data_files:
+  - split: train
+    path: monash_m3_other/train-*
+- config_name: monash_m3_quarterly
+  data_files:
+  - split: train
+    path: monash_m3_quarterly/train-*
+- config_name: monash_m3_yearly
+  data_files:
+  - split: train
+    path: monash_m3_yearly/train-*
+- config_name: nn5_daily_with_missing
+  data_files:
+  - split: train
+    path: nn5_daily_with_missing/train-*
+- config_name: nn5_weekly
+  data_files:
+  - split: train
+    path: nn5_weekly/train-*
+- config_name: oikolab_weather
+  data_files:
+  - split: train
+    path: oikolab_weather/train-*
+- config_name: pedestrian_counts
+  data_files:
+  - split: train
+    path: pedestrian_counts/train-*
+- config_name: project_tycho
+  data_files:
+  - split: train
+    path: project_tycho/train-*
+- config_name: residential_load_power
+  data_files:
+  - split: train
+    path: residential_load_power/train-*
+- config_name: residential_pv_power
+  data_files:
+  - split: train
+    path: residential_pv_power/train-*
+- config_name: rideshare_with_missing
+  data_files:
+  - split: train
+    path: rideshare_with_missing/train-*
+- config_name: sceaux
+  data_files:
+  - split: train
+    path: sceaux/train-*
+- config_name: smart
+  data_files:
+  - split: train
+    path: smart/train-*
+- config_name: solar_power
+  data_files:
+  - split: train
+    path: solar_power/train-*
+- config_name: subseasonal
+  data_files:
+  - split: train
+    path: subseasonal/train-*
+- config_name: subseasonal_precip
+  data_files:
+  - split: train
+    path: subseasonal_precip/train-*
+- config_name: sunspot_with_missing
+  data_files:
+  - split: train
+    path: sunspot_with_missing/train-*
+- config_name: taxi_30min
+  data_files:
+  - split: train
+    path: taxi_30min/train-*
+- config_name: tourism_monthly
+  data_files:
+  - split: train
+    path: tourism_monthly/train-*
+- config_name: tourism_quarterly
+  data_files:
+  - split: train
+    path: tourism_quarterly/train-*
+- config_name: tourism_yearly
+  data_files:
+  - split: train
+    path: tourism_yearly/train-*
+- config_name: traffic_hourly
+  data_files:
+  - split: train
+    path: traffic_hourly/train-*
+- config_name: traffic_weekly
+  data_files:
+  - split: train
+    path: traffic_weekly/train-*
+- config_name: uber_tlc_daily
+  data_files:
+  - split: train
+    path: uber_tlc_daily/train-*
+- config_name: uber_tlc_hourly
+  data_files:
+  - split: train
+    path: uber_tlc_hourly/train-*
+- config_name: vehicle_trips_with_missing
+  data_files:
+  - split: train
+    path: vehicle_trips_with_missing/train-*
+- config_name: weather
+  data_files:
+  - split: train
+    path: weather/train-*
+- config_name: wiki-rolling_nips
+  data_files:
+  - split: train
+    path: wiki-rolling_nips/train-*
+- config_name: wind_farms_with_missing
+  data_files:
+  - split: train
+    path: wind_farms_with_missing/train-*
+- config_name: wind_power
+  data_files:
+  - split: train
+    path: wind_power/train-*
 ---
 
+
 # GiftEval Pretrain (Derived)
 
 This dataset is a derived version of [Salesforce/GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), the pre-training dataset aligned with the [GIFT-Eval](https://huggingface.co/datasets/Salesforce/GiftEval) benchmark for time series foundation models.