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Time Series Transformer Tourism Monthly

Developed by huggingface
This is a time series forecasting model based on Transformer architecture, trained for 30 epochs on the tourism-monthly dataset.
Downloads 4,595
Release Time : 9/26/2022

Model Overview

The model adopts an encoder-decoder architecture specifically designed for time series forecasting tasks, capable of generating predictions step-by-step in an autoregressive manner.

Model Features

Autoregressive Prediction
The model can generate predictions step-by-step in an autoregressive manner, forecasting one timestep at a time.
Transformer Architecture
Utilizes standard encoder-decoder Transformer architecture, well-suited for processing time series data.
Professional Dataset Training
Thoroughly trained on the monash_tsf/tourism-monthly professional time series dataset.

Model Capabilities

Time Series Forecasting
Multi-step Prediction
Autoregressive Generation

Use Cases

Tourism Industry
Monthly Visitor Volume Prediction
Forecasting future monthly visitor trends for tourist attractions
Business Forecasting
Sales Trend Prediction
Predicting product sales for future months
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