Instructions to use Alred/bart-base-finetuned-summarization-cnn-ver3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alred/bart-base-finetuned-summarization-cnn-ver3 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="Alred/bart-base-finetuned-summarization-cnn-ver3")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Alred/bart-base-finetuned-summarization-cnn-ver3") model = AutoModelForSeq2SeqLM.from_pretrained("Alred/bart-base-finetuned-summarization-cnn-ver3") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on the section config and train split of ccdv/pubmed-summarization
#3
by autoevaluator HF Staff - opened
Beep boop, I am a bot from Hugging Face's automatic model evaluator π!
Your model has been evaluated on the section config and train split of the ccdv/pubmed-summarization dataset by @Vishnu196 , using the predictions stored here.
Accept this pull request to see the results displayed on the Hub leaderboard.
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