Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Small_2018_Global with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Small_2018_Global with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Small_2018_Global") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Small_2018_Global") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3faf1cab472b01ba651f1447091710641330858b598377030f9d5204f53f2e2
- Size of remote file:
- 185 MB
- SHA256:
- 9c7bd6df0338196f0909d0220a3588acddd2f5cccd6b24773d7e3137455350ba
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.