Instructions to use y-oikawa/Information-triage-for-disaster-tweets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use y-oikawa/Information-triage-for-disaster-tweets with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="y-oikawa/Information-triage-for-disaster-tweets")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("y-oikawa/Information-triage-for-disaster-tweets") model = AutoModelForSequenceClassification.from_pretrained("y-oikawa/Information-triage-for-disaster-tweets") - Notebooks
- Google Colab
- Kaggle
ELECTRA Base Japanese for Information Triage
This is an ELECTRA model pretrained on approximately 200M Japanese sentences additionally finetuned for Information Triage.
The model was based on transformers-ud-japanese-electra-base-discriminator, and later finetuned on a dataset containing disaster tweets.
Licenses
The finetuned model with all attached files is licensed under CC BY-SA 4.0, or Creative Commons Attribution-ShareAlike 4.0 International License.
Citations
Please, cite this model using the following citation.
@inproceedings{oikawa2022electra-base-triage,
title={北見工業大学 テキスト情報処理研究室 ELECTRA Base 情報トリアージモデル (megagon labs ver.)},
author={及川 佑人 and プタシンスキ ミハウ and 桝井 文人},
publisher={HuggingFace},
year={2022},
url = "https://huggingface.co/y-oikawa/Information-triage-for-disaster-tweets"
}
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