Summarization
Transformers
PyTorch
Core ML
Safetensors
English
t5
text2text-generation
medical
text-generation-inference
Instructions to use Falconsai/medical_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/medical_summarization 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="Falconsai/medical_summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Falconsai/medical_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("Falconsai/medical_summarization") - Inference
- Notebooks
- Google Colab
- Kaggle
Add medical tag
#3
by davanstrien HF Staff - opened
README.md
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in prague , prvouk p34 and unce 204010/2012 . funding to pay the open access
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publication charges for this article was provided by iga mz r nt12094/2011 .
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example_title: Summarization Example 1
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in prague , prvouk p34 and unce 204010/2012 . funding to pay the open access
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publication charges for this article was provided by iga mz r nt12094/2011 .
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example_title: Summarization Example 1
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tags:
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- medical
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