Time Series Forecasting
Transformers
Safetensors
kairos
time-series
forecasting
foundation-model
zero-shot
Instructions to use mldi-lab/Kairos_10m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mldi-lab/Kairos_10m with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mldi-lab/Kairos_10m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add `pipeline_tag` and `library_name` to model card
#1
by nielsr HF Staff - opened
This PR enhances the model card for Kairos-10M by adding the following metadata:
pipeline_tag: time-series-forecasting: This improves the model's discoverability on the Hugging Face Hub by categorizing it under the appropriate task.library_name: transformers: This indicates compatibility with the Hugging Facetransformerslibrary, enabling the automated "How to use" widget and providing users with a direct code snippet for loading the model. Evidence fortransformerscompatibility comes from theAutoModel.from_pretrainedusage in the code snippet and thetransformers_versionin theconfig.json.
The existing model card content, including paper links, GitHub repository, project page, and sample usage, remains unchanged as it is already comprehensive and accurate.
GritLs changed pull request status to merged