Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Tiny_2023_Augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Tiny_2023_Augmented with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Tiny_2023_Augmented") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Tiny_2023_Augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ccc4b24d299b5d18a765b6a7ee71c074dc4cecbc9a496dd18660a300a0a68bc
- Size of remote file:
- 33.6 MB
- SHA256:
- c42f7ae9c27281a8a72a122df43134b8af9cb17a3a2c88ec5b888858daf23a13
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.