Instructions to use leduckhai/ViT5-VietMedSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leduckhai/ViT5-VietMedSum 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="leduckhai/ViT5-VietMedSum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("leduckhai/ViT5-VietMedSum") model = AutoModelForSeq2SeqLM.from_pretrained("leduckhai/ViT5-VietMedSum") - Notebooks
- Google Colab
- Kaggle
Improve model card: correct pipeline tag, add paper link, and refine description
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Correcting the
pipeline_tagtoaudio-text-to-text. - Adding a link to the paper on the Hugging Face Hub.
- Refining the model description to be more concise and informative.