Spaces:
Sleeping
Sleeping
| title: News Summarizer and NER | |
| emoji: 🏢 | |
| colorFrom: green | |
| colorTo: indigo | |
| sdk: streamlit | |
| sdk_version: 1.29.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| #### New Summarization and NER | |
| News summarization uses "facebook/bart-base" that is fine-tuned using TensorFlow for summarization using | |
| <a href = "https://www.kaggle.com/datasets/gowrishankarp/newspaper-text-summarization-cnn-dailymail" target="_blank">CNN news articles</a> dataset.<br><br> | |
| NER uses "microsoft/deberta-base" that is fine-tuned using TensorFlow for token classification (NER) using this | |
| <a href="https://www.kaggle.com/datasets/saurabhprajapat/named-entity-recognition" target="_blank">dataset</a>.<br>The fine-tuning dataset contains annotated sentences.<br> | |
| During inference, the input text is split into sentences using Spacy and entities are identified in each sentence.<br> | |
| The notebook to fine-tune "facebook/bart-base" for news summarization can be found <a href="https://github.com/ksv-muralidhar/hugging_face_tf_fine_tuning/blob/main/bart_en_summarization.ipynb">here</a>.<br> | |
| The notebook to fine-tune "microsoft/deberta-base" for NER can be found <a href="https://github.com/ksv-muralidhar/hugging_face_tf_fine_tuning/blob/main/ner_deberta.ipynb">here</a>. |