Token Classification
spaCy
Arabic
arabic
named-entity-recognition
ner
finance
financial-ner
information-extraction
ontology-aligned
Eval Results (legacy)
Instructions to use Muhsabrys/AMWAL_ArFinNER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Muhsabrys/AMWAL_ArFinNER with spaCy:
!pip install https://huggingface.co/Muhsabrys/AMWAL_ArFinNER/resolve/main/AMWAL_ArFinNER-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("AMWAL_ArFinNER") # Importing as module. import AMWAL_ArFinNER nlp = AMWAL_ArFinNER.load() - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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@@ -67,7 +67,7 @@ from amwal import load_ner
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ner = load_ner()
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text = "
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result = ner(text)
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print(result["entities"])
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from amwal import load_ner
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ner = load_ner()
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result = ner("نص عربي م
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```
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---
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ner = load_ner()
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text = "يطرح البنك المركزي المصري، بعد غد، سندات خزانة ثابتة ومتغيرة العائد بقيمة 45 مليار جنيه"
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result = ner(text)
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print(result["entities"])
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from amwal import load_ner
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ner = load_ner()
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result = ner("يطرح البنك المركزي المصري، بعد غد، سندات خزانة ثابتة ومتغيرة العائد بقيمة 45 مليار جنيه")
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print(result["entities"])
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[{'text': 'البنك المركزي المصري', 'label': 'BANK', 'start': 5, 'end': 25}, {'text': 'سندات', 'label': 'FINANCIAL_INSTRUMENT', 'start': 35, 'end': 40}, {'text': '45 مليار', 'label': 'QUNATITY_OR_UNIT', 'start': 74, 'end': 82}, {'text': 'جنيه', 'label': 'CURRENCY', 'start': 83, 'end': 87}]
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```
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---
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