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I want to tag entities in a sentence , for that purpose I am using bert and ner predictor.
I tried to use shap on the ner predictor but the ner predictor gets as an input a 3D tensor
(X[0] contains …
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Hi, I followed this tutorial with the sample data.
https://github.com/uf-hobi-informatics-lab/ClinicalTransformerNER/blob/master/tutorial/pipeline_preprocessing_model_training_prediction.ipynb
Ev…
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Hi. I want to finetune a model on data where some of them do not contain entities (so that there is less fp). I tried to do it with such examples in the dataset:
{'tokenized_text': ['In', 'this', 'ye…
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when i run 'run_ner.py' show some error like this:
run_ner.py: error: the following arguments are required: --task_type, --task_save_name, --data_dir, --data_name, --model_n
ame, --model_name_or_pat…
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Hi,
Thank you guys for your work and codes. But I am a little confused that can your work be considered zero-shot or few-shot NER? Because you used a full-supervised fine-tuned NER model for Datas…
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### Is there an existing issue for this?
- [X] I have searched the existing issues and did not find a match.
### Who can help?
_No response_
### What are you working on?
I am training NerDLApproa…
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**Describe the bug**
Take the following sentence: **Assurez-vous d'être à l'heure !**
The word vous has a wrong dependency relation with Stanza 1.8.2, but correct with Stanza 1.8.1
Stanza 1.8.1 :…
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### Describe the bug
Hello,
I was trying to fine tune a mT5 model (google/mT5 series models) on a custom dataset that follows the text format given in your documentation for the column data load…
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**Describe the solution you'd like**…