Instructions to use sumedh/biomedical_text_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumedh/biomedical_text_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="sumedh/biomedical_text_summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sumedh/biomedical_text_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("sumedh/biomedical_text_summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d77e252d5fb4c7f8177e99801e796d72f7f18b34aa1f6f2d3c0cabcdd25ecb06
- Size of remote file:
- 3.13 GB
- SHA256:
- 27096f10f2606a3bc19b9b1b8a461cb652fc47c1f33401ecd55fba4846c7778a
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