Instructions to use Mia2024/CS5100TextSummarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mia2024/CS5100TextSummarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Mia2024/CS5100TextSummarization") model = AutoModelForSeq2SeqLM.from_pretrained("Mia2024/CS5100TextSummarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Mia2024/CS5100TextSummarization: direct link, hf CLI and curl.
- Browser
- Download file 694 Bytes
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https://huggingface.co/Mia2024/CS5100TextSummarization/resolve/main/README.md
- Command line
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hf download hf://Mia2024/CS5100TextSummarization/README.md
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curl -L -o README.md https://huggingface.co/Mia2024/CS5100TextSummarization/resolve/main/README.md
694 Bytes
| library_name: transformers | |
| license: mit | |
| datasets: | |
| - knkarthick/dialogsum | |
| language: | |
| - en | |
| metrics: | |
| - rouge | |
| # Model Card for Model ID | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| ## Model Details | |
| ### Model Description | |
| Final Project for 2024 Fall CS5100 Foundations of Artificial Intelligence at Roux Institute, Northeastern University. | |
| * Developed by: Nan Chen | |
| * Language(s) (NLP): Python, Transformers | |
| * Finetuned from model: facebook/bart-large-cnn | |
| ### Model Sources [optional] | |
| - **Repository:** Final folder in [Github CS6120NLP](https://github.com/awakn123/CS6120NLP) | |
| - **Demo:** [Space link](https://huggingface.co/spaces/Mia2024/CS5100TextSummarization). | |