Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Tiny_2012_Global with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Tiny_2012_Global with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Tiny_2012_Global") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Tiny_2012_Global", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cbf4d872e55c555716164ce039ce25ccc69b2eb21aed807d1cbf631bc52c2a2
- Size of remote file:
- 33.6 MB
- SHA256:
- a120decd830f651b897984274b16b61bc46cbeb87f9a07d0ca73539b3e991007
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.