Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Small_2023_Augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Small_2023_Augmented with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Small_2023_Augmented") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Small_2023_Augmented") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc09118ebda1df66d4207959bbb0b2b5c74e9c35d7b54380e144e6280af5bafc
- Size of remote file:
- 185 MB
- SHA256:
- a9aa2de7432184b07773cd457651e9b7fdee7d0c4b32bab19329862d5f87f246
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