Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Mini_2014_Augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Mini_2014_Augmented with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Mini_2014_Augmented") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Mini_2014_Augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5dc506d74d0111569a1f966f20357cf4c017d96f539b369a312c4ff72f6e473
- Size of remote file:
- 81.8 MB
- SHA256:
- 8eebc3080c90b27be7b54bfa7d17d00c44d96da31e3b7b05bc5181b5ee77348c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.