Text Classification
Transformers
Safetensors
yield-weather-soil
crop-yield
multi-temporal
regression
yield-estimation
custom_code
Instructions to use ICICLE-AI/yield-estimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ICICLE-AI/yield-estimation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ICICLE-AI/yield-estimation", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("ICICLE-AI/yield-estimation", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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This model uses the USA County Level Crop Yield Dataset.
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```bibtex
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@inproceedings{hasan2026vita,
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title={VITA: Variational Pretraining of Transformers for Climate-Robust Crop Yield Forecasting},
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author={Adib Hasan and Mardavij Roozbehani and Munther Dahleh},
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booktitle={Proceedings of the 40th AAAI Conference on Artificial Intelligence},
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year={2026},
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url={https://arxiv.org/abs/2508.03589},
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}
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@article{Khaki2020CNNRNN,
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author = {Khaki, Saeed and Wang, Liang and Archontoulis, Sotirios V.},
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This model uses the USA County Level Crop Yield Dataset.
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```bibtex
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@article{Khaki2020CNNRNN,
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author = {Khaki, Saeed and Wang, Liang and Archontoulis, Sotirios V.},
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