Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Mini_2019_US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Mini_2019_US with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Mini_2019_US") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Mini_2019_US") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e10e8a47cc596a7e83eb93bcdd4d5ad397d90bd12b181ca4a27e4fb66984a13
- Size of remote file:
- 81.8 MB
- SHA256:
- c93567fa7ef33de51f409ccd02b2edc36344ca3e834aaaead15f02173cb81a37
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.