Time Series Forecasting
Transformers
Safetensors
Timer-S1
time series
time-series
forecasting
foundation models
pretrained models
time series foundation models
custom_code
Instructions to use bytedance-research/Timer-S1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bytedance-research/Timer-S1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bytedance-research/Timer-S1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from bytedance-research/Timer-S1: direct link, hf CLI and curl.
- Browser
- Download file 50 Bytes
-
https://huggingface.co/bytedance-research/Timer-S1/resolve/main/.gitattributes
- Command line
-
hf download hf://bytedance-research/Timer-S1/.gitattributes
-
curl -L -o .gitattributes https://huggingface.co/bytedance-research/Timer-S1/resolve/main/.gitattributes
50 Bytes
| *.safetensors filter=lfs diff=lfs merge=lfs -text | |