Spaces:
Running
on
Zero
Running
on
Zero
Update README.md
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README.md
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title: Named Entity Recognition
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sdk: gradio
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sdk_version: 4.
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app_file: app.py
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pinned: false
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license: afl-3.0
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title: Named Entity Recognition
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emoji: ππ·οΈ
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sdk: gradio
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sdk_version: 4.41.0
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app_file: app.py
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pinned: false
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license: afl-3.0
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# Named Entity Recognition (NER) App
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This application provides a simple interface to perform Named Entity Recognition (NER) on text using a pre-trained model from Hugging Face's Transformers library. The model used under the hood is `dslim/bert-base-NER`, which is designed to identify entities such as names, locations, organizations, and more in a given text.
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## Features
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- **Named Entity Recognition**: Automatically identify and highlight entities within a given text.
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- **User-Friendly Interface**: Built using Gradio for an easy-to-use web interface.
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## Model
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- **Model Used**: [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER)
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- **Framework**: Hugging Face Transformers
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## Software Packages
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- **Gradio**: Used to create the web interface.
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- **Transformers**: Used for model inference.
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- **Spaces**: Utilized for GPU acceleration during model execution.
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## How to Use
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1. Enter the text you want to analyze in the "Text to find entities" textbox.
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2. Click "Submit" to perform Named Entity Recognition.
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3. The identified entities will be highlighted in the output box.
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