Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Tiny_2018_Augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Tiny_2018_Augmented with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Tiny_2018_Augmented") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Tiny_2018_Augmented") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ad2a6d05608c460f6ee4c9afc6d49d1a01dfa049ac973904f4950fe219bc2dc
- Size of remote file:
- 33.6 MB
- SHA256:
- 458546dc06bb070643eb9e04bd5e75abc4a5c8aa0ec2816762f2058c1e9d6f01
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.