Time series / Model
Toto-2.0-2.5B-FT
- Organisation
- Datadog
- Family
- Toto · version 2.0
- Released
- 2026-05-19 (arXiv v1 submission date of the technical report that describes it (https://arxiv.org/abs/2605.20119); HF repo Datadog/Toto-2.0-2.5B-FT createdAt 2026-05-12 (HF API).)
- Checkpoints
- Datadog/Toto-2.0-2.5B-FT
- Weights
- Open · apache-2.0
- Links
- PaperModel cardCode
Training data disclosure: Partial list
Level determined for 73% of benchmark cells.
- TestTest data seen0
- SeenSeen, split unclear1
- TrainTraining data seen28
- Related data seen7
- NoNot seen0
- ?Unknown13
“The full mix was: GIFT-Eval Pretrain (45%), Datadog 5+ minute metrics (25%), GIFT-Eval train (15%), synthetic (10%), and Datadog 10 s and 60 s metrics (2.5% each)”
Training corpora
-
GIFT-Eval Pretrain (GiftEvalPretrain)
· 86 sources (complete list) · pre-training
· homepage
Evidence that Toto-2.0-2.5B-FT uses it
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
huggingface.co · model card · Finetuning recipe · retrieved 2026-10-15 Contents of this corpus
-
BDG-2 Panther · split: unknown
HF folder(s): bdg-2_panther.
Evidence
“BDG-2 Panther”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
BDG-2 Fox · split: unknown
HF folder(s): bdg-2_fox.
Evidence
“BDG-2 Fox BDG-2 Rat”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
BDG-2 Rat · split: unknown
HF folder(s): bdg-2_rat.
Evidence
“BDG-2 Rat BDG-2 Bear”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
BDG-2 Bear · split: unknown
HF folder(s): bdg-2_bear.
Evidence
“BDG-2 Bear”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Low Carbon London · split: unknown
HF folder(s): lcl.
Evidence
“Low Carbon London”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
SMART · split: unknown
HF folder(s): smart.
Evidence
“SMART IDEAL”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
IDEAL · split: unknown
HF folder(s): ideal.
Evidence
“IDEAL Sceaux”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Sceaux · split: unknown
HF folder(s): sceaux.
Evidence
“Sceaux Borealis”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Borealis · split: unknown
HF folder(s): borealis.
Evidence
“Borealis Buildings900K”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Buildings900K · split: unknown
HF folder(s): buildings_900k.
Evidence
“Buildings900K”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
CMIP6 · split: unknown
HF folder(s): cmip6_1850 ... cmip6_2010 (33 folders, every 5 years).
Evidence
“CMIP6 ERA5”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
ERA5 · split: unknown
HF folder(s): era5_1989 ... era5_2018 (30 yearly folders).
Evidence
“ERA5 Azure VM Traces 2017”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Azure VM Traces 2017 · split: unknown
HF folder(s): azure_vm_traces_2017.
Evidence
“Azure VM Traces 2017”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Borg Cluster Data 2011 · split: unknown
HF folder(s): borg_cluster_data_2011.
Evidence
“Borg Cluster Data 2011”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Alibaba Cluster Trace 2018 · split: unknown
HF folder(s): alibaba_cluster_trace_2018.
Evidence
“Alibaba Cluster Trace 2018”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Taxi · split: unknown
HF folder(s): taxi_30min.
Evidence
“Taxi Uber TLC Daily”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Uber TLC Daily · split: unknown
HF folder(s): uber_tlc_daily.
Evidence
“Uber TLC Daily”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Uber TLC Hourly · split: unknown
HF folder(s): uber_tlc_hourly.
Evidence
“Uber TLC Hourly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Wiki-Rolling · split: unknown
HF folder(s): wiki-rolling_nips.
Evidence
“Wiki-Rolling”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
M5 · split: unknown
HF folder(s): m5.
Evidence
“M5 LargeST”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
LargeST (PeMS California) · split: unknown
HF folder(s): largest_2017 ... largest_2021 (5 yearly folders).
Evidence
“LargeST PEMS03”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
PEMS03 · split: unknown
HF folder(s): PEMS03.
Evidence
“PEMS03 PEMS04”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
PEMS04 · split: unknown
HF folder(s): PEMS04.
Evidence
“PEMS04 PEMS07”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
PEMS07 · split: unknown
HF folder(s): PEMS07.
Evidence
“PEMS07 PEMS08”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
PEMS08 · split: unknown
HF folder(s): PEMS08.
Evidence
“PEMS08 PEMS Bay”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
PEMS Bay · split: unknown
HF folder(s): PEMS_BAY.
Evidence
“PEMS Bay Los-Loop”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Los-Loop · split: unknown
HF folder(s): LOS_LOOP.
Evidence
“Los-Loop Beijing Subway”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Beijing Subway · split: unknown
HF folder(s): BEIJING_SUBWAY_30MIN.
Evidence
“Beijing Subway”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
SHMetro · split: unknown
HF folder(s): SHMETRO.
Evidence
“SHMetro HZMetro”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
HZMetro · split: unknown
HF folder(s): HZMETRO.
Evidence
“HZMetro Q-Traffic”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Q-Traffic · split: unknown
HF folder(s): Q-TRAFFIC.
Evidence
“Q-Traffic Subseasonal”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Subseasonal · split: unknown
HF folder(s): subseasonal.
Evidence
“Subseasonal”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Subseasonal Precipitation · split: unknown
HF folder(s): subseasonal_precip.
Evidence
“Subseasonal Precipitation”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Covid19 Energy · split: unknown
HF folder(s): covid19_energy.
Evidence
“Covid19 Energy”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
GEF12 · split: unknown
HF folder(s): gfc12_load.
Evidence
“GEF12 GEF14”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
GEF14 · split: unknown
HF folder(s): gfc14_load.
Evidence
“GEF14 GEF17”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
GEF17 · split: unknown
HF folder(s): gfc17_load.
Evidence
“GEF17 PDB Spanish”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
PDB · split: unknown
HF folder(s): pdb.
Evidence
“PDB Spanish”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Spanish · split: unknown
HF folder(s): spain.
Evidence
“Spanish BDG-2 Hog”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
BDG-2 Hog · split: unknown
HF folder(s): hog.
Evidence
“BDG-2 Hog BDG-2 Bull”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
BDG-2 Bull · split: unknown
HF folder(s): bull.
Evidence
“BDG-2 Bull”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
BDG-2 Cockatoo · split: unknown
HF folder(s): cockatoo.
Evidence
“BDG-2 Cockatoo”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
ELF · split: unknown
HF folder(s): elf.
Evidence
“ELF London Smart Meters”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
London Smart Meters · split: unknown
HF folder(s): london_smart_meters_with_missing.
Evidence
“London Smart Meters”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Wind Farms · split: unknown
HF folder(s): wind_farms_with_missing.
Evidence
“Wind Farms”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Wind Power · split: unknown
HF folder(s): wind_power.
Evidence
“Wind Power”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Solar Power · split: unknown
HF folder(s): solar_power. AEMO 4-second solar power (Monash), not the LSTNet Alabama solar dataset in the GIFT-Eval test set.
Evidence
“Solar Power”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Oikolab Weather · split: unknown
HF folder(s): oikolab_weather.
Evidence
“Oikolab Weather”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Elecdemand · split: unknown
HF folder(s): elecdemand.
Evidence
“Elecdemand”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Covid Mobility · split: unknown
HF folder(s): covid_mobility.
Evidence
“Covid Mobility”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Kaggle Web Traffic Weekly · split: unknown
HF folder(s): kaggle_web_traffic_weekly.
Evidence
“Kaggle Web Traffic Weekly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Extended Web Traffic · split: unknown
HF folder(s): extended_web_traffic_with_missing.
Evidence
“Extended Web Traffic”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
M1 Yearly · split: unknown
HF folder(s): m1_yearly.
Evidence
“M1 Yearly M1 Quarterly”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
M1 Quarterly · split: unknown
HF folder(s): m1_quarterly.
Evidence
“M1 Quarterly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
M1 Monthly · split: unknown
HF folder(s): m1_monthly.
Evidence
“M1 Monthly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
M3 Yearly · split: unknown
HF folder(s): monash_m3_yearly.
Evidence
“M3 Yearly M3 Quarterly”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
M3 Quarterly · split: unknown
HF folder(s): monash_m3_quarterly.
Evidence
“M3 Quarterly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
M3 Monthly · split: unknown
HF folder(s): monash_m3_monthly.
Evidence
“M3 Monthly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
M3 Other · split: unknown
HF folder(s): monash_m3_other.
Evidence
“M3 Other NN5 Daily”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
NN5 Daily · split: unknown
HF folder(s): nn5_daily_with_missing.
Evidence
“NN5 Daily NN5 Weekly”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
NN5 Weekly · split: unknown
HF folder(s): nn5_weekly.
Evidence
“NN5 Weekly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Tourism Yearly · split: unknown
HF folder(s): tourism_yearly.
Evidence
“Tourism Yearly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Tourism Quarterly · split: unknown
HF folder(s): tourism_quarterly.
Evidence
“Tourism Quarterly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Tourism Monthly · split: unknown
HF folder(s): tourism_monthly.
Evidence
“Tourism Monthly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
CIF 2016 · split: unknown
HF folder(s): cif_2016_12, cif_2016_6.
Evidence
“CIF 2016 Traffic Weekly”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Traffic Weekly (Monash) · split: unknown
HF folder(s): traffic_weekly. Monash weekly aggregation of the 862-sensor traffic dataset (registry id monash-traffic-weekly).
Evidence
“Traffic Weekly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Traffic (PeMS San Francisco Bay, 862 sensors) · split: unknown
HF folder(s): traffic_hourly. Monash 'traffic_hourly' = the 862-sensor San Francisco traffic dataset of LSTNet, i.e. the long-horizon Traffic dataset (registry id traffic-862).
Evidence
“Traffic Hourly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Australian Electricity Demand · split: unknown
HF folder(s): australian_electricity_demand.
Evidence
“Australian Electricity Demand”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Rideshare · split: unknown
HF folder(s): rideshare_with_missing.
Evidence
“Rideshare Sunspot”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Sunspot · split: unknown
HF folder(s): sunspot_with_missing.
Evidence
“Sunspot Vehicle Trips”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Vehicle Trips · split: unknown
HF folder(s): vehicle_trips_with_missing.
Evidence
“Vehicle Trips”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Weather · split: unknown
HF folder(s): weather. Monash 'weather' (Australian BOM, 3,010 daily series; Table 14 source column: Monash), NOT the Jena weather data used in GIFT-Eval and long-horizon.
Evidence
“Weather FRED MD”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
FRED MD · split: unknown
HF folder(s): fred_md.
Evidence
“FRED MD Pedestrian Counts”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Pedestrian Counts · split: unknown
HF folder(s): pedestrian_counts.
Evidence
“Pedestrian Counts”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Bitcoin · split: unknown
HF folder(s): bitcoin_with_missing.
Evidence
“Bitcoin KDD Cup 2022”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
KDD Cup 2022 · split: unknown
HF folder(s): kdd2022. Not the KDD Cup 2018 air-quality dataset that is in the GIFT-Eval test set.
Evidence
“KDD Cup 2022”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
GoDaddy · split: unknown
HF folder(s): godaddy.
Evidence
“GoDaddy Favorita Sales”
arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15 -
Favorita Sales · split: unknown
HF folder(s): favorita_sales.
Evidence
“Favorita Sales”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Favorita Transactions · split: unknown
HF folder(s): favorita_transactions.
Evidence
“Favorita Transactions”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
China Air Quality · split: unknown
HF folder(s): china_air_quality.
Evidence
“China Air Quality”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Beijing Air Quality · split: unknown
HF folder(s): beijing_air_quality.
Evidence
“Beijing Air Quality”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Residential Load Power · split: unknown
HF folder(s): residential_load_power.
Evidence
“Residential Load Power”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Residential PV Power · split: unknown
HF folder(s): residential_pv_power.
Evidence
“Residential PV Power”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
CDC FluView ILINet (LOTSA) · split: unknown
HF folder(s): cdc_fluview_ilinet. Same source (CDC FluView) as the long-horizon ILI dataset (registry id cdc-fluview-ilinet).
Evidence
“CDC Fluview ILINet”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
CDC Fluview WHO NREVSS · split: unknown
HF folder(s): cdc_fluview_who_nrevss.
Evidence
“CDC Fluview WHO NREVSS”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15 -
Project Tycho · split: unknown
HF folder(s): project_tycho.
Evidence
“Project Tycho”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
-
BDG-2 Panther · split: unknown
Other declared training data
-
Jena Weather (GIFT-Eval) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
BizITObs - Application · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
BizITObs - Service · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
BizITObs - L2C · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Bitbrains - Fast Storage · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Bitbrains - rnd · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Restaurant (Recruit Restaurant Visitor Forecasting) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
ETT1 (GIFT-Eval) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
ETT2 (GIFT-Eval) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Loop Seattle (LibCity) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
SZ-Taxi (LibCity) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
M_DENSE (LibCity) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Solar (LSTNet, 137 Alabama PV plants) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Hierarchical Sales (Mancuso et al., 2020) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
M4 Yearly · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
M4 Quarterly · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
M4 Monthly · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
M4 Weekly · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
M4 Daily · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
M4 Hourly · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Hospital · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
COVID Deaths · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
US Births · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Saugeen River Flow · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Temperature Rain · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
KDD Cup 2018 · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Car Parts · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
ElectricityLoadDiagrams20112014 (UCI) · split: train of gift-eval
Finetuning (not pretraining) data; 15% of the finetuning mix. Covers the GIFT-Eval evaluation datasets' official train splits.
Evidence
“finetuned on a mix that **includes the GIFT-Eval training split**”
huggingface.co · model card · What this is · retrieved 2026-10-15 “and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15 -
Chronos pretraining corpus (not yet matched to a dataset) · split: unknown
Same public pool as Toto 1.0 (Chronos datasets minus GIFT-Eval overlap).
Evidence
“with the GIFT-Eval Pretrain portion drawn from the Toto 1.0 public-data pool of GIFT-Eval Pretrain and the Chronos pretraining corpus (Ansari et al., 2024) (non-leaking).”
arxiv.org · paper · Section 5.3 · retrieved 2026-10-15
Declared exclusions
-
Benchmark GIFT-Eval · test portion excluded
Evidence
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
huggingface.co · model card · Finetuning recipe · retrieved 2026-10-15
Benchmark cells
GIFT-Eval
Training data seen Jena Weather (GIFT-Eval) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen BizITObs - Application · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen BizITObs - Service · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen BizITObs - L2C · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Bitbrains - Fast Storage · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Bitbrains - rnd · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Restaurant (Recruit Restaurant Visitor Forecasting) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen ETT1 (GIFT-Eval) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen ETT2 (GIFT-Eval) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Loop Seattle (LibCity) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen SZ-Taxi (LibCity) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen M_DENSE (LibCity) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Solar (LSTNet, 137 Alabama PV plants) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Hierarchical Sales (Mancuso et al., 2020) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen M4 Yearly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen M4 Quarterly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen M4 Monthly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen M4 Weekly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen M4 Daily · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen M4 Hourly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Hospital · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen COVID Deaths · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen US Births · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Saugeen River Flow · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Temperature Rain · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen KDD Cup 2018 · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen Car Parts · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Training data seen ElectricityLoadDiagrams20112014 (UCI) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded
Evidence (3)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
Long-horizon forecasting (ETT, Electricity, Traffic, Weather, Exchange, ILI)
ETTh1 · related dataset ETT1 (GIFT-Eval) was used
Evidence (4)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“From Informer (Zhou et al., 2021) we utilize ETT1 and ETT2 datasets, which denote electricity transformer temperature”
“ETTh1&ETTh2 7 17,420”
ETTh2 · related dataset ETT2 (GIFT-Eval) was used
Evidence (4)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“From Informer (Zhou et al., 2021) we utilize ETT1 and ETT2 datasets, which denote electricity transformer temperature”
“ETTh1&ETTh2 7 17,420”
ETTm1 · related dataset ETT1 (GIFT-Eval) was used
Evidence (4)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“From Informer (Zhou et al., 2021) we utilize ETT1 and ETT2 datasets, which denote electricity transformer temperature”
“ETTm1 &ETTm2 7 69,680”
ETTm2 · related dataset ETT2 (GIFT-Eval) was used
Evidence (4)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“From Informer (Zhou et al., 2021) we utilize ETT1 and ETT2 datasets, which denote electricity transformer temperature”
“ETTm1 &ETTm2 7 69,680”
Electricity (ECL, 321 clients) · related dataset ElectricityLoadDiagrams20112014 (UCI) was used
Evidence (5)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“The raw dataset is in https://archive.ics.uci.edu/ml/datasets/ElectricityLoadDiagrams20112014.”
“Because the some dimensions are equal to 0. So we eliminate the records in 2011. Final we get data contains electircity consumption of 321 clients from 2012 to 2014.”
“https://archive.ics.uci.edu/ml/datasets/ElectricityLoadDiagrams20112014”
Seen, split unclear Traffic (PeMS San Francisco Bay, 862 sensors) · the dataset was used; the source does not say which part (via GIFT-Eval Pretrain (GiftEvalPretrain))
Evidence (2)
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
“Traffic Hourly”
Weather (Jena, 2020; Autoformer) · related dataset Jena Weather (GIFT-Eval) was used
Evidence (5)
“finetuned on a mix that **includes the GIFT-Eval training split**”
“and the official train splits of those evaluation datasets themselves (Aksu et al., 2024b), which we refer to as GIFT-Eval train.”
“We incorporate Jena Weather5 dataset following Autoformer (Wu et al., 2021).”
“is recorded every 10 minutes for 2020 whole year, which contains 21 meteorological indicators, such as air temperature, humidity, etc.”
“https://www.bgc-jena.mpg.de/wetter/”
Unknown Exchange-Rate · training data not disclosed in enough detail
ILI (CDC influenza-like illness, national) · related dataset CDC FluView ILINet (LOTSA) was used (via GIFT-Eval Pretrain (GiftEvalPretrain))
Evidence (5)
“The public portion (45% GIFT-Eval Pretrain) is drawn from the Toto 1.0 mix of GIFT-Eval Pretrain and the Chronos pretraining corpus, and is non-leaking with respect to the GIFT-Eval test split.”
“CDC Fluview ILINet”
“includes the weekly recorded influenza-like illness (ILI) patients data from Centers for Disease Control and Prevention of the United States between 2002 and 2021”
“https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html”
“CDC Fluview ILINet CDC Fluview WHO NREVSS”
Time-series anomaly detection
Unknown TSB-AD-U (TSB-AD univariate) · training data not disclosed in enough detail
Unknown TSB-AD-M (TSB-AD multivariate) · training data not disclosed in enough detail
Unknown UCR Time Series Anomaly Archive (Hexagon ML/UCR, KDD Cup 2021) · training data not disclosed in enough detail
Unknown Server Machine Dataset (SMD) · training data not disclosed in enough detail
Unknown Mars Science Laboratory (MSL) telemetry anomaly dataset · training data not disclosed in enough detail
Unknown Soil Moisture Active Passive (SMAP) telemetry anomaly dataset · training data not disclosed in enough detail
Unknown Pooled Server Metrics (PSM) · training data not disclosed in enough detail
Unknown Secure Water Treatment (SWaT) · training data not disclosed in enough detail
Unknown Yahoo S5 Labeled Anomaly Detection Dataset (Yahoo Webscope S5) · training data not disclosed in enough detail
Unknown Numenta Anomaly Benchmark (NAB) · training data not disclosed in enough detail
Time-series classification
Unknown UCR Time Series Classification Archive (2018) · training data not disclosed in enough detail
Unknown UEA Multivariate Time Series Classification Archive (2018) · training data not disclosed in enough detail
Notes
Benchmark-only checkpoint: Toto 2.0 2.5B finetuned 10,000 steps on GIFT-Eval Pretrain (45%), Datadog metrics (30%), GIFT-Eval train split (15%) and TempoPFN synthetic (10%). It is a finetuned (not zero-shot) GIFT-Eval submission. The companion Toto-2.0-Family-and-Friends is an XGBoost-gated ensemble of 10 foundation models (not a separately pretrained model) and is not listed as a model here.
Sources
- Toto-2.0-2.5B-FT model card · model card · retrieved 2026-10-15
- Toto 2.0 technical report (arXiv v2) · paper · retrieved 2026-10-15