Instructions to use niltonseixas/summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use niltonseixas/summarizer with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("niltonseixas/summarizer", set_active=True) - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse filesfirst version of card
README.md
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---
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language:
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- pt
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library_name: adapter-transformers
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---
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# Summarizer
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<!-- Provide a quick summary of what the model is/does. -->
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THis model aims to summarize general texts. It is just for studying porposes.
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [Nilton Seixas]
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- **Language(s) (NLP):** [English]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [t5-small]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [niltonseixas/summarizer]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Example
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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```
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from transformers import pipeline
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```
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summarizer = pipeline("summarization", model="my_awesome_billsum_model")
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text = """summarize: The Inflation Reduction Act lowers prescription drug costs, health care costs,
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and energy costs. It's the most aggressive action on tackling the climate crisis in American history,
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which will lift up American workers and create good-paying, union jobs across the country.
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It'll lower the deficit and ask the ultra-wealthy and corporations to pay their fair share.
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And no one making under $400,000 per year will pay a penny more in taxes."""
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summarizer(text)
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