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Adding ONNX file of this model
Beep boop I am the [ONNX export bot 🤖🏎️](https://huggingface.co/spaces/onnx/export). On behalf of [Bencle](https://huggingface.co/Bencle), I would like to add to this repository the model converted to ONNX. What is ONNX? It stands for "Open Neural Network Exchange", and is the most commonly used open standard for machine learning interoperability. You can find out more at [onnx.ai](https://onnx.ai/)! The exported ONNX model can be then be consumed by various backends as TensorRT or TVM, or simply be used in a few lines with 🤗 Optimum through ONNX Runtime, check out how [here](https://huggingface.co/docs/optimum/main/en/onnxruntime/usage_guides/models)!804cc19
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (1b1f1b5278a4e757ea98c46d2afb40c29aacc5a8) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>a371ace -
Update README.md (#3)
- Update README.md (5d799c07ef240089e35fcd6365b25b97cc70daff) Co-authored-by: Janusz Wilczek <Jawi@users.noreply.huggingface.co>17b12d2 -
Add evaluation results on the conll2003 config and test split of conll2003 (#1)
- Add evaluation results on the conll2003 config and test split of conll2003 (bf7ca2f490fe8968093aabbe5a00b8bd41c40cf1) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>6dadf25
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--- language: en datasets: - conll2003 --- # bert-large-NER ## Model description **bert-large-NER** is a fine-tuned BERT-Large model that is ready to use for **Named Entity Recognition** and achieves **state-of-the-art performance** for the NER task. It has been trained to recognize four types of entities: location (LOC), organizations (ORG), person (PER) and Miscellaneous (MISC). Specifically, this model is a *bert-large-cased* model that was fine-tuned on the English version of the standard [CoNLL-2003 Named Entity Recognition](https://www.aclweb.org/anthology/W03-0419.pdf) dataset. If you'd like to use a smaller model fine-tuned on the same dataset, a [bert-base-cased](https://huggingface.co/dslim/bert-base-NER) version is also available. ## Intended uses & limitations #### How to use You can use this model with Transformers *pipeline* for NER. ```python from transformers import AutoTokenizer, AutoModelForTokenClassification from transformers import…de53cbc
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