Instructions to use marcosgg/bert-base-gl-SLI-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcosgg/bert-base-gl-SLI-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="marcosgg/bert-base-gl-SLI-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("marcosgg/bert-base-gl-SLI-NER") model = AutoModelForTokenClassification.from_pretrained("marcosgg/bert-base-gl-SLI-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add multilingual to the language tag
Browse filesHi! A PR to add multilingual to the language tag to improve the referencing.
README.md
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license: gpl-3.0
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language:
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- gl
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# Named Entity Recognition (NER) model for Galician
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language:
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- gl
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- multilingual
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license: gpl-3.0
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widget:
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- text: A mi�a amiga Rosa, de Lisboa, estudou en Montreal. Agora traballa en Nova
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Pescanova.
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# Named Entity Recognition (NER) model for Galician
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