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
Update README.md
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README.md
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@@ -95,6 +95,7 @@ def post_process_re_output(re_output, re_input, ner_output):
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>>> print("Sentence: ",re_ner_output["input"])
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>>> print("Entity: ", re_ner_output["entity"])
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>>> print("Relation: ", re_ner_output["relation"])
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### BibTeX entry and citation info
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>>> print("Sentence: ",re_ner_output["input"])
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>>> print("Entity: ", re_ner_output["entity"])
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>>> print("Relation: ", re_ner_output["relation"])
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```
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### BibTeX entry and citation info
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