Time Series Forecasting
Transformers
PyTorch
Korean
jnu_tsb
feature-extraction
jnu-tsb
time-series
forecasting
chronos-2
polyglot-ko
korean
finance
covariates
r
reticulate
education
custom_code
Instructions to use HONGRIZON/JNU-TSB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HONGRIZON/JNU-TSB with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HONGRIZON/JNU-TSB", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47a314203aabcbfddec52cad60c00763b0d18070464a6205c5ee4adea10f84f6
- Size of remote file:
- 1.62 kB
- SHA256:
- ee70794f4c8b7feed2ca6cfa91f3226ccfd5f22e19eb5d5f223beff4f4e479a1
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