Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
time series
forecasting
pretrained models
foundation models
time series foundation models
time-series
text-generation-inference
Instructions to use autogluon/chronos-t5-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autogluon/chronos-t5-tiny with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("autogluon/chronos-t5-tiny") model = AutoModelForMultimodalLM.from_pretrained("autogluon/chronos-t5-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65b5d6ee61e35a10fe4d9ae71a09729617130b96671bfd4ffecff2fad1171e57
- Size of remote file:
- 33.6 MB
- SHA256:
- a6ff6a769165b77ddbb1d2f1f90822e359da5e429052531ca90b93ab19d11732
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