Instructions to use akdeniz27/mDeBERTa-v3-base-turkish-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akdeniz27/mDeBERTa-v3-base-turkish-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="akdeniz27/mDeBERTa-v3-base-turkish-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("akdeniz27/mDeBERTa-v3-base-turkish-ner") model = AutoModelForTokenClassification.from_pretrained("akdeniz27/mDeBERTa-v3-base-turkish-ner") - Notebooks
- Google Colab
- Kaggle
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- text: "Mustafa Kemal Atatürk 19 Mayıs 1919'da Samsun'a çıktı."
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# Turkish Named Entity Recognition (NER) Model
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This model is the fine-tuned version of "mDeBERTa-v3-base"
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(a multilingual version of DeBERTa V3)
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using a reviewed version of well known Turkish NER dataset
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(https://github.com/stefan-it/turkish-bert/files/4558187/nerdata.txt).
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- text: "Mustafa Kemal Atatürk 19 Mayıs 1919'da Samsun'a çıktı."
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---
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# Turkish Named Entity Recognition (NER) Model
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This model is the fine-tuned version of "microsoft/mDeBERTa-v3-base"
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(a multilingual version of DeBERTa V3)
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using a reviewed version of well known Turkish NER dataset
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(https://github.com/stefan-it/turkish-bert/files/4558187/nerdata.txt).
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