Initial upload of parquet dataset configs

README.md

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+---
+configs:
+- config_name: bitbrains_fast_storage_5T_long
+  data_files:
+  - split: train
+    path: bitbrains_fast_storage_5T_long/train.parquet
+- config_name: bitbrains_fast_storage_5T_medium
+  data_files:
+  - split: train
+    path: bitbrains_fast_storage_5T_medium/train.parquet
+- config_name: bitbrains_fast_storage_5T_short
+  data_files:
+  - split: train
+    path: bitbrains_fast_storage_5T_short/train.parquet
+- config_name: bitbrains_fast_storage_H_short
+  data_files:
+  - split: train
+    path: bitbrains_fast_storage_H_short/train.parquet
+- config_name: bitbrains_rnd_5T_long
+  data_files:
+  - split: train
+    path: bitbrains_rnd_5T_long/train.parquet
+- config_name: bitbrains_rnd_5T_medium
+  data_files:
+  - split: train
+    path: bitbrains_rnd_5T_medium/train.parquet
+- config_name: bitbrains_rnd_5T_short
+  data_files:
+  - split: train
+    path: bitbrains_rnd_5T_short/train.parquet
+- config_name: bitbrains_rnd_H_short
+  data_files:
+  - split: train
+    path: bitbrains_rnd_H_short/train.parquet
+- config_name: bizitobs_application_10S_long
+  data_files:
+  - split: train
+    path: bizitobs_application_10S_long/train.parquet
+- config_name: bizitobs_application_10S_medium
+  data_files:
+  - split: train
+    path: bizitobs_application_10S_medium/train.parquet
+- config_name: bizitobs_application_10S_short
+  data_files:
+  - split: train
+    path: bizitobs_application_10S_short/train.parquet
+- config_name: bizitobs_l2c_5T_long
+  data_files:
+  - split: train
+    path: bizitobs_l2c_5T_long/train.parquet
+- config_name: bizitobs_l2c_5T_medium
+  data_files:
+  - split: train
+    path: bizitobs_l2c_5T_medium/train.parquet
+- config_name: bizitobs_l2c_5T_short
+  data_files:
+  - split: train
+    path: bizitobs_l2c_5T_short/train.parquet
+- config_name: bizitobs_l2c_H_long
+  data_files:
+  - split: train
+    path: bizitobs_l2c_H_long/train.parquet
+- config_name: bizitobs_l2c_H_medium
+  data_files:
+  - split: train
+    path: bizitobs_l2c_H_medium/train.parquet
+- config_name: bizitobs_l2c_H_short
+  data_files:
+  - split: train
+    path: bizitobs_l2c_H_short/train.parquet
+- config_name: bizitobs_service_10S_long
+  data_files:
+  - split: train
+    path: bizitobs_service_10S_long/train.parquet
+- config_name: bizitobs_service_10S_medium
+  data_files:
+  - split: train
+    path: bizitobs_service_10S_medium/train.parquet
+- config_name: bizitobs_service_10S_short
+  data_files:
+  - split: train
+    path: bizitobs_service_10S_short/train.parquet
+- config_name: car_parts_M_short
+  data_files:
+  - split: train
+    path: car_parts_M_short/train.parquet
+- config_name: covid_deaths_D_short
+  data_files:
+  - split: train
+    path: covid_deaths_D_short/train.parquet
+- config_name: electricity_15T_long
+  data_files:
+  - split: train
+    path: electricity_15T_long/train.parquet
+- config_name: electricity_15T_medium
+  data_files:
+  - split: train
+    path: electricity_15T_medium/train.parquet
+- config_name: electricity_15T_short
+  data_files:
+  - split: train
+    path: electricity_15T_short/train.parquet
+- config_name: electricity_D_short
+  data_files:
+  - split: train
+    path: electricity_D_short/train.parquet
+- config_name: electricity_H_long
+  data_files:
+  - split: train
+    path: electricity_H_long/train.parquet
+- config_name: electricity_H_medium
+  data_files:
+  - split: train
+    path: electricity_H_medium/train.parquet
+- config_name: electricity_H_short
+  data_files:
+  - split: train
+    path: electricity_H_short/train.parquet
+- config_name: electricity_W_short
+  data_files:
+  - split: train
+    path: electricity_W_short/train.parquet
+- config_name: ett1_15T_long
+  data_files:
+  - split: train
+    path: ett1_15T_long/train.parquet
+- config_name: ett1_15T_medium
+  data_files:
+  - split: train
+    path: ett1_15T_medium/train.parquet
+- config_name: ett1_15T_short
+  data_files:
+  - split: train
+    path: ett1_15T_short/train.parquet
+- config_name: ett1_D_short
+  data_files:
+  - split: train
+    path: ett1_D_short/train.parquet
+- config_name: ett1_H_long
+  data_files:
+  - split: train
+    path: ett1_H_long/train.parquet
+- config_name: ett1_H_medium
+  data_files:
+  - split: train
+    path: ett1_H_medium/train.parquet
+- config_name: ett1_H_short
+  data_files:
+  - split: train
+    path: ett1_H_short/train.parquet
+- config_name: ett1_W_short
+  data_files:
+  - split: train
+    path: ett1_W_short/train.parquet
+- config_name: ett2_15T_long
+  data_files:
+  - split: train
+    path: ett2_15T_long/train.parquet
+- config_name: ett2_15T_medium
+  data_files:
+  - split: train
+    path: ett2_15T_medium/train.parquet
+- config_name: ett2_15T_short
+  data_files:
+  - split: train
+    path: ett2_15T_short/train.parquet
+- config_name: ett2_D_short
+  data_files:
+  - split: train
+    path: ett2_D_short/train.parquet
+- config_name: ett2_H_long
+  data_files:
+  - split: train
+    path: ett2_H_long/train.parquet
+- config_name: ett2_H_medium
+  data_files:
+  - split: train
+    path: ett2_H_medium/train.parquet
+- config_name: ett2_H_short
+  data_files:
+  - split: train
+    path: ett2_H_short/train.parquet
+- config_name: ett2_W_short
+  data_files:
+  - split: train
+    path: ett2_W_short/train.parquet
+- config_name: hierarchical_sales_D_short
+  data_files:
+  - split: train
+    path: hierarchical_sales_D_short/train.parquet
+- config_name: hierarchical_sales_W_short
+  data_files:
+  - split: train
+    path: hierarchical_sales_W_short/train.parquet
+- config_name: hospital_M_short
+  data_files:
+  - split: train
+    path: hospital_M_short/train.parquet
+- config_name: jena_weather_10T_long
+  data_files:
+  - split: train
+    path: jena_weather_10T_long/train.parquet
+- config_name: jena_weather_10T_medium
+  data_files:
+  - split: train
+    path: jena_weather_10T_medium/train.parquet
+- config_name: jena_weather_10T_short
+  data_files:
+  - split: train
+    path: jena_weather_10T_short/train.parquet
+- config_name: jena_weather_D_short
+  data_files:
+  - split: train
+    path: jena_weather_D_short/train.parquet
+- config_name: jena_weather_H_long
+  data_files:
+  - split: train
+    path: jena_weather_H_long/train.parquet
+- config_name: jena_weather_H_medium
+  data_files:
+  - split: train
+    path: jena_weather_H_medium/train.parquet
+- config_name: jena_weather_H_short
+  data_files:
+  - split: train
+    path: jena_weather_H_short/train.parquet
+- config_name: kdd_cup_2018_D_short
+  data_files:
+  - split: train
+    path: kdd_cup_2018_D_short/train.parquet
+- config_name: kdd_cup_2018_H_long
+  data_files:
+  - split: train
+    path: kdd_cup_2018_H_long/train.parquet
+- config_name: kdd_cup_2018_H_medium
+  data_files:
+  - split: train
+    path: kdd_cup_2018_H_medium/train.parquet
+- config_name: kdd_cup_2018_H_short
+  data_files:
+  - split: train
+    path: kdd_cup_2018_H_short/train.parquet
+- config_name: loop_seattle_5T_long
+  data_files:
+  - split: train
+    path: loop_seattle_5T_long/train.parquet
+- config_name: loop_seattle_5T_medium
+  data_files:
+  - split: train
+    path: loop_seattle_5T_medium/train.parquet
+- config_name: loop_seattle_5T_short
+  data_files:
+  - split: train
+    path: loop_seattle_5T_short/train.parquet
+- config_name: loop_seattle_D_short
+  data_files:
+  - split: train
+    path: loop_seattle_D_short/train.parquet
+- config_name: loop_seattle_H_long
+  data_files:
+  - split: train
+    path: loop_seattle_H_long/train.parquet
+- config_name: loop_seattle_H_medium
+  data_files:
+  - split: train
+    path: loop_seattle_H_medium/train.parquet
+- config_name: loop_seattle_H_short
+  data_files:
+  - split: train
+    path: loop_seattle_H_short/train.parquet
+- config_name: m4_daily_D_short
+  data_files:
+  - split: train
+    path: m4_daily_D_short/train.parquet
+- config_name: m4_hourly_H_short
+  data_files:
+  - split: train
+    path: m4_hourly_H_short/train.parquet
+- config_name: m4_monthly_M_short
+  data_files:
+  - split: train
+    path: m4_monthly_M_short/train.parquet
+- config_name: m4_quarterly_Q_short
+  data_files:
+  - split: train
+    path: m4_quarterly_Q_short/train.parquet
+- config_name: m4_weekly_W_short
+  data_files:
+  - split: train
+    path: m4_weekly_W_short/train.parquet
+- config_name: m4_yearly_A_short
+  data_files:
+  - split: train
+    path: m4_yearly_A_short/train.parquet
+- config_name: m_dense_D_short
+  data_files:
+  - split: train
+    path: m_dense_D_short/train.parquet
+- config_name: m_dense_H_long
+  data_files:
+  - split: train
+    path: m_dense_H_long/train.parquet
+- config_name: m_dense_H_medium
+  data_files:
+  - split: train
+    path: m_dense_H_medium/train.parquet
+- config_name: m_dense_H_short
+  data_files:
+  - split: train
+    path: m_dense_H_short/train.parquet
+- config_name: restaurant_D_short
+  data_files:
+  - split: train
+    path: restaurant_D_short/train.parquet
+- config_name: saugeen_D_short
+  data_files:
+  - split: train
+    path: saugeen_D_short/train.parquet
+- config_name: saugeen_M_short
+  data_files:
+  - split: train
+    path: saugeen_M_short/train.parquet
+- config_name: saugeen_W_short
+  data_files:
+  - split: train
+    path: saugeen_W_short/train.parquet
+- config_name: solar_10T_long
+  data_files:
+  - split: train
+    path: solar_10T_long/train.parquet
+- config_name: solar_10T_medium
+  data_files:
+  - split: train
+    path: solar_10T_medium/train.parquet
+- config_name: solar_10T_short
+  data_files:
+  - split: train
+    path: solar_10T_short/train.parquet
+- config_name: solar_D_short
+  data_files:
+  - split: train
+    path: solar_D_short/train.parquet
+- config_name: solar_H_long
+  data_files:
+  - split: train
+    path: solar_H_long/train.parquet
+- config_name: solar_H_medium
+  data_files:
+  - split: train
+    path: solar_H_medium/train.parquet
+- config_name: solar_H_short
+  data_files:
+  - split: train
+    path: solar_H_short/train.parquet
+- config_name: solar_W_short
+  data_files:
+  - split: train
+    path: solar_W_short/train.parquet
+- config_name: sz_taxi_15T_long
+  data_files:
+  - split: train
+    path: sz_taxi_15T_long/train.parquet
+- config_name: sz_taxi_15T_medium
+  data_files:
+  - split: train
+    path: sz_taxi_15T_medium/train.parquet
+- config_name: sz_taxi_15T_short
+  data_files:
+  - split: train
+    path: sz_taxi_15T_short/train.parquet
+- config_name: sz_taxi_H_short
+  data_files:
+  - split: train
+    path: sz_taxi_H_short/train.parquet
+- config_name: temperature_rain_D_short
+  data_files:
+  - split: train
+    path: temperature_rain_D_short/train.parquet
+- config_name: us_births_D_short
+  data_files:
+  - split: train
+    path: us_births_D_short/train.parquet
+- config_name: us_births_M_short
+  data_files:
+  - split: train
+    path: us_births_M_short/train.parquet
+- config_name: us_births_W_short
+  data_files:
+  - split: train
+    path: us_births_W_short/train.parquet
+---
+# GiftEval Parquet Collection
+
+This repository hosts the parquet formatted GiftEval test data for ease of evaluating with LLM backboned models. Each dataset in the original GiftEval dataset can be loaded separately using the config names: `datasetName_freq_term`. Each row is a sample window from the test split of data, generated using the original GiftEval [proressing script](https://github.com/SalesforceAIResearch/gift-eval).
+
+Each entry contains the following fields:
+- **item_id** (string): e.g. "item_0_dim0_window0/2018-04-12 20:00:00"
+- **frequency** (string): e.g. "15T"
+- **history_start** (string): e.g. "2016-07-01 00:00:00"
+- **history_end** (string): e.g. "2018-04-12 19:45:00"
+- **history_value** (list): e.g. [1,3,3,4,5,6,7,...]
+- **future_start** (string): e.g. "2018-04-12 20:00:00"
+- **future_end** (string): e.g. "2018-04-20 07:45:00"
+- **future_value** (list): e.g. [8,9,10,...]
+- **config** (string): e.g. "ett1/15T/long"
+
+
+Note: that multivariate datasets are split into univariate form so each row is a univariate sample. The dimension information is saved within item_id.
+
+## Example usage
+  ```python
+    from datasets import load_dataset
+
+    ds = load_dataset(
+        "Salesforce/GiftEvalParquet",
+        "bitbrains_fast_storage_5T_long",
+        split="train"
+    )
+    print(len(ds))
+    print(ds[0].keys)
+
+
+  ```
+
+# Citation
+If you find this benchmark useful, please consider citing:
+
+```
+@article{aksu2024giftevalbenchmarkgeneraltime,
+      title={GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation}, 
+      author={Taha Aksu and Gerald Woo and Juncheng Liu and Xu Liu and Chenghao Liu and Silvio Savarese and Caiming Xiong and Doyen Sahoo},
+      journal = {arxiv preprint arxiv:2410.10393},
+      year={2024},
+}
+```
+    

bitbrains_fast_storage_5T_long/train.parquet

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