Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Tiny_2020_Augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Tiny_2020_Augmented with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Tiny_2020_Augmented") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Tiny_2020_Augmented") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb1498148865810589cf66594e9f48e09510ae7015eb53891eaab1d866d4b1fd
- Size of remote file:
- 33.6 MB
- SHA256:
- ff7fe8d8a58ac81e8bb2cd7a44e43fd834f126854c7ba95ed920c0adb325bb51
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.