Instructions to use xtie/BART-PET-impression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xtie/BART-PET-impression with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="xtie/BART-PET-impression")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("xtie/BART-PET-impression") model = AutoModelForSeq2SeqLM.from_pretrained("xtie/BART-PET-impression", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# Automatic Personalized Impression Generation for PET Reports Using Large Language Models 📄✍
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**Authored by**: Xin Tie, Muheon Shin, Ali Pirasteh, Nevein Ibrahim, Zachary Huemann, Sharon M. Castellino, Kara Kelly, John Garrett, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw
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language: en
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tags:
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- summarization
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- medical
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# Automatic Personalized Impression Generation for PET Reports Using Large Language Models 📄✍
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**Authored by**: Xin Tie, Muheon Shin, Ali Pirasteh, Nevein Ibrahim, Zachary Huemann, Sharon M. Castellino, Kara Kelly, John Garrett, Junjie Hu, Steve Y. Cho, Tyler J. Bradshaw
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