Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Mini_2017_Augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Mini_2017_Augmented with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Mini_2017_Augmented") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Mini_2017_Augmented") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 586ae4e05d73aedfccf830982c267224978377732683d9560f687ca8aaeeb520
- Size of remote file:
- 81.8 MB
- SHA256:
- cc20a138aff3a9d18866b3e54f3a9cb210c541924838091fa0117cda6c0181ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.