Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Small_2006_Global with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Small_2006_Global with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Small_2006_Global") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Small_2006_Global") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e719caa10932e9df7a63c6a6ce76a65d65d2dae587fac7432fb600ad38d8cd74
- Size of remote file:
- 185 MB
- SHA256:
- 7947aeb23dfdb6112440b22d19688b5a7c43288684eacba54d8b589dab4f2c49
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.