Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Tiny_2016_Global with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Tiny_2016_Global with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Tiny_2016_Global") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Tiny_2016_Global") - Notebooks
- Google Colab
- Kaggle
metadata
pipeline_tag: time-series-forecasting
license: apache-2.0
tags:
- TSFM
- Finance
- Financial Forecasting
- FinText
library_name: transformers
Chronos-Tiny (TSFM) โ Global (2016)
This is the Time Series Foundation Model (TSFM), pre-trained on global financial time series data up to the year 2016 using the Chronos architecture (Tiny size). The dataset spans from 1990โ2016 and includes all global excess return data.
๐ Related Links