https://github.com/warjohn/nlp-ner
A simple NLP-NER project for named entity recognition using character-level labeling and transformer-based token classification.
https://github.com/warjohn/nlp-ner
deep-learning natural-language-processing ner nlp python
Last synced: about 1 month ago
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A simple NLP-NER project for named entity recognition using character-level labeling and transformer-based token classification.
- Host: GitHub
- URL: https://github.com/warjohn/nlp-ner
- Owner: warjohn
- License: mit
- Created: 2025-05-18T11:39:21.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-18T12:10:53.000Z (about 1 year ago)
- Last Synced: 2025-06-24T08:43:57.079Z (about 1 year ago)
- Topics: deep-learning, natural-language-processing, ner, nlp, python
- Language: Jupyter Notebook
- Homepage:
- Size: 503 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# NLP-NER
The task of the project: search for an entity in a sentence, in this case, a product article. The BERT model was taken as a basis for additional training. Symbolic vectorization was used. And a tokenizer pre-trained from the same model.
## Getting Started
1) Create python-env and activate
```bash
python3 -m venv venv
source venv/bin/activate
```
2) install dependences
```python
pip install -r req.txt
```
## Usage
- File -> ```final.ipynb``` This file describes the process of training the model
- File -> ```test.ipynb``` This file is about how to use the model in the future.
- Dir -> ```ner_model``` contains model's checkpoints
## License
This project is licensed under the [License Name] - see the [LICENSE](LICENSE) file for details.
## Contacts
- **Telegram**: [@Menar_qq](https://t.me/Menar_qq)
- **Gmail**: [johnvoronina@gmail.com](mailto:johnvoronina@gmail.com)