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--- |
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license: apache-2.0 |
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language: |
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- en |
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metrics: |
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- bleu |
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- rouge |
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base_model: |
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- facebook/bart-large-cnn |
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pipeline_tag: summarization |
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tags: |
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- medical |
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--- |
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# My Summarization Model 📝 |
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## Model Description |
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This model is a fine-tuned version of `facebook/bart-large-cnn` on medical text data. It is designed for text summarization tasks and can generate concise summaries for lengthy medical documents, making it useful for healthcare professionals and researchers. |
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### Model Type |
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- **Architecture**: BART (Bidirectional and Auto-Regressive Transformers) |
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- **Pre-trained Base Model**: [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) |
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## How to Use |
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You can use the model directly with the Hugging Face `transformers` library: |
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```python |
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from transformers import pipeline |
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summarizer = pipeline("summarization", model="Abdelrahman-Hassan-1/Medical-RAG-Model") |
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text = """Your long medical text here.""" |
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summary = summarizer(text) |
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print(summary) |
