ajitrajasekharan commited on
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Update app.py

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  1. app.py +1 -1
app.py CHANGED
@@ -1,7 +1,7 @@
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  import gradio as gr
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  title = "Model for Biomedical NER"
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  description = "Gradio Demo of a pretrained model used for NER without fine-tuning. To test model predictions, simply add your text, or click one of the examples to load them. These predictions are used to perform NER as described in the link below."
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- article = "<p style='text-align: center'><a href='https://ajitrajasekharan.github.io/2021/01/02/my-first-post.html' target='_blank'>Model pretrained on biomedical corpus and used for NER without fine-tuning</a> | <a href='https://huggingface.co/ajitrajasekharan/biomedical' target='_blank'>HF model page</a></p><p style='text-align: left; color: #6f6f6f'><a href='https://huggingface.co/spaces/ajitrajasekharan/Qualitative-pretrained-model-evaluation' target='_blank'><br/><i>Note:Streamlit version of this app is a better choice to examine model than this app:- <br/>- Control over number of results to display<br/>- Examine both masked position and [CLS] predictions <br/>- Compare this model results with other pretrained BERT models.</i></a></p>"
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  examples = [
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  ["Lou Gehrig who works for XCorp suffers from [MASK]"],["A [MASK] level below 60 indicates chronic kidney disease"],["There are no specific treatment options specifically indicated for [MASK]"],["Paul Erdos died at [MASK]"]
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  ]
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  import gradio as gr
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  title = "Model for Biomedical NER"
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  description = "Gradio Demo of a pretrained model used for NER without fine-tuning. To test model predictions, simply add your text, or click one of the examples to load them. These predictions are used to perform NER as described in the link below."
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+ article = "<p style='text-align: center'><a href='https://ajitrajasekharan.github.io/2021/01/02/my-first-post.html' target='_blank'>Model pretrained on biomedical corpus and used for NER without fine-tuning</a> | <a href='https://huggingface.co/ajitrajasekharan/biomedical' target='_blank'>HF model page</a></p><p style='text-align: left; color: #6f6f6f'><a href='https://huggingface.co/spaces/ajitrajasekharan/Qualitative-pretrained-model-evaluation' target='_blank'><br/><I><u>Note:Streamlit version of this app is a better choice to examine model than this app:-</u> <br/>- Control over number of results to display<br/>- Examine both masked position and [CLS] predictions <br/>- Compare this model results with other pretrained BERT models.</i></a></p>"
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  examples = [
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  ["Lou Gehrig who works for XCorp suffers from [MASK]"],["A [MASK] level below 60 indicates chronic kidney disease"],["There are no specific treatment options specifically indicated for [MASK]"],["Paul Erdos died at [MASK]"]
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  ]