Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Small_2023_US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Small_2023_US with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Small_2023_US") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Small_2023_US", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12dbdb51f00e7b290739990234321a01635118888bc421c4371c623ad5aa7a59
- Size of remote file:
- 185 MB
- SHA256:
- 794d945d2dc068926242862c8080f3f98d456cb96244034fda18f7d589dc31b5
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