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NER_model_holako
Holako/NER_model_holako
NER_model_holako is a token classification model from Holako. Use it when you need labels on individual words, such as names. It is set up for transformers.
You can use this model with Transformers pipeline for NER.
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Repo size
4.5 GB
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Feb 23, 2022
- SHA
- b358aa4f
Try a prompt
Model card
From the Hugging Face model README
How to use
You can use this model with Transformers pipeline for NER.
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
tokenizer = AutoTokenizer.from_pretrained("Holako/NER_model_holako")
model = AutoModelForTokenClassification.from_pretrained("Holako/NER_model_holako")
nlp = pipeline("ner", model=model, tokenizer=tokenizer)
example = "اسمي احمد"
ner_results = nlp(example)
print(ner_results)
Limitations and bias
This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains.
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Limitations and bias
This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains.
Training data
| Language | Dataset |
|---|---|
| Arabic | ANERcorp |
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Mar 2, 2022
- Updated
- Feb 23, 2022