Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Tiny_2000_US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Tiny_2000_US with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Tiny_2000_US") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Tiny_2000_US", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 513d35385704d45b05f899970e1922e34db2062ec817fa5849109f88f85c388b
- Size of remote file:
- 33.6 MB
- SHA256:
- 0193aa3d8a9d71f84d082c31c715810eb48a57c6a2ed3d7864da243c4056aa5a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.