Token Classification
Transformers
PyTorch
bert
feature-extraction
entity-recognition
foundation-model
mBERT
Multilingual Bert
BERT
generic
Instructions to use numind/NuNER-multilingual-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use numind/NuNER-multilingual-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="numind/NuNER-multilingual-v0.1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("numind/NuNER-multilingual-v0.1") model = AutoModel.from_pretrained("numind/NuNER-multilingual-v0.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Citation
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@misc{bogdanov2024nuner,
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title={NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data},
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author={Sergei Bogdanov and Alexandre Constantin and Timothée Bernard and Benoit Crabbé and Etienne Bernard},
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eprint={2402.15343},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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## Citation
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```
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@misc{bogdanov2024nuner,
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title={NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data},
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author={Sergei Bogdanov and Alexandre Constantin and Timothée Bernard and Benoit Crabbé and Etienne Bernard},
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eprint={2402.15343},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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