Instructions to use m-lin20/satellite-instrument-bert-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m-lin20/satellite-instrument-bert-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="m-lin20/satellite-instrument-bert-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("m-lin20/satellite-instrument-bert-NER") model = AutoModelForTokenClassification.from_pretrained("m-lin20/satellite-instrument-bert-NER") - Notebooks
- Google Colab
- Kaggle
satellite-instrument-bert-NER
For details, please visit the GitHub link.
Citation
Our paper has been published in the International Journal of Digital Earth :
@article{lin2022satellite,
title={Satellite and instrument entity recognition using a pre-trained language model with distant supervision},
author={Lin, Ming and Jin, Meng and Liu, Yufu and Bai, Yuqi},
journal={International Journal of Digital Earth},
volume={15},
number={1},
pages={1290--1304},
year={2022},
publisher={Taylor \& Francis}
}
- Downloads last month
- 2