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:
- 7e63d2da96865dd2ce463f729f1426236704184bc3c6e21f1fb59209a1c30de9
- Size of remote file:
- 33.6 MB
- SHA256:
- eed458758bd8165d80f496a90bcd2cfed9f1bf7d7b08677acd64e0f7d72bdcf2
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