Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Mini_2023_US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Mini_2023_US with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Mini_2023_US") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Mini_2023_US") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78442ce965df49e0c03aab8964b0b12e097d88ef7077be9874e9f296edff0a49
- Size of remote file:
- 81.8 MB
- SHA256:
- f184c911cd8cbe255a62327953b71fbcdb2bf0501a532b1ac85cde35cfe67b12
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.