Text Classification
Transformers
PyTorch
TensorFlow
TensorBoard
Arabic
English
bert
BERT
Text Classification
relation
text-embeddings-inference
Instructions to use ychenNLP/arabic-relation-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ychenNLP/arabic-relation-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ychenNLP/arabic-relation-extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ychenNLP/arabic-relation-extraction") model = AutoModelForSequenceClassification.from_pretrained("ychenNLP/arabic-relation-extraction") - Notebooks
- Google Colab
- Kaggle
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# Arabic Relation Extraction Model
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- Relation Extraction model based on [GigaBERTv4](https://huggingface.co/lanwuwei/GigaBERT-v4-Arabic-and-English).
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- ACE2005 Training data: Arabic
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- [Relation tags](https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/arabic-relations-guidelines-v6.5.pdf) including: Physical, Part-whole, Personal-Social, 'ORG-Affiliation, Agent-Artifact, Gen-Affiliation
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# Arabic Relation Extraction Model
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- [Github repo](https://github.com/edchengg/GigaBERT)
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- Relation Extraction model based on [GigaBERTv4](https://huggingface.co/lanwuwei/GigaBERT-v4-Arabic-and-English).
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- ACE2005 Training data: Arabic
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- [Relation tags](https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/arabic-relations-guidelines-v6.5.pdf) including: Physical, Part-whole, Personal-Social, 'ORG-Affiliation, Agent-Artifact, Gen-Affiliation
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