# Time Series Forecasting

ChatTime-1-7B-Base is a foundational model specialized in time series forecasting, supporting multimodal time series processing.

ChatTime-1-7B-Chat is a multimodal foundation model specialized in time series forecasting, built on a 7B parameter scale.

This model is designed for time series forecasting, supports the English language, and uses a specific license (bethana15).

A time series forecasting model based on the PatchTSMixer architecture, developed by IBM, suitable for multivariate time series forecasting tasks.

IBM Granite series time series forecasting model, based on PatchTST architecture, suitable for various time series forecasting tasks.

This is a pre-trained time series forecasting model, focusing on time series data analysis and prediction tasks.

Chronos is a family of pre-trained time series forecasting models based on language model architecture, which transforms time series into token sequences for training through quantization and scaling.

PatchTSMixer is a time series forecasting foundational model under IBM's Granite project, featuring an innovative Patch hybrid architecture suitable for various time series forecasting tasks.

PatchTST is a pre-trained time series foundation model, focusing on time series forecasting tasks.

ChatTime is an innovative multimodal time series foundation model that treats time series as a foreign language, unifying the processing of bimodal input/output for both time series and text.

Chronos is a family of pretrained time series forecasting models based on language model architecture, which supports probabilistic forecasting by converting time series into token sequences for training.

Chronos is a family of pretrained time series forecasting models based on language model architectures, trained by quantizing and scaling time series into token sequences.

Chronos is a family of pretrained time series forecasting models based on language model architectures, trained by converting time series into token sequences, supporting probabilistic forecasting.

Chronos is a family of pretrained time series forecasting models based on language model architectures, trained by quantizing and scaling time series into token sequences.

Chronos is a family of pre-trained time series forecasting models based on language model architecture, which transforms time series into token sequences for training to achieve probabilistic forecasting.

Chronos is a family of pre-trained time series forecasting models based on language model architectures. It converts time series into token sequences through quantization and scaling for training, suitable for probabilistic forecasting tasks.

Chronos-T5 is a pretrained time series forecasting model based on a language model architecture, achieving probabilistic forecasting by converting time series into token sequences and training the language model using cross-entropy loss.