Time Series Forecasting
Transformers
PyTorch
patchtst
Generated from Trainer
time series
forecasting
pretrained models
foundation models
time series foundation models
time-series
Instructions to use ibm-research/patchtst-etth1-pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-research/patchtst-etth1-pretrain with Transformers:
# Load model directly from transformers import AutoTokenizer, PatchTSTForMaskPretraining tokenizer = AutoTokenizer.from_pretrained("ibm-research/patchtst-etth1-pretrain") model = PatchTSTForMaskPretraining.from_pretrained("ibm-research/patchtst-etth1-pretrain") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 045468d530c9323b1dc92129189d59926eb2e52fd5030ae7aaf4f8217dc09e15
- Size of remote file:
- 4.85 MB
- SHA256:
- 685c0e0c6ba52af4a140cb57a2eed46330efa9660d9a6f7ecf2c5edc8b050f48
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