Instructions to use ainize/bart-base-cnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ainize/bart-base-cnn 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="ainize/bart-base-cnn")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ainize/bart-base-cnn") model = AutoModel.from_pretrained("ainize/bart-base-cnn") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on the default config and test split of xsum
#6 opened over 2 years ago
by
autoevaluator
Add evaluation results on the samsum config and test split of samsum
#5 opened over 2 years ago
by
autoevaluator
Add evaluation results on the 3.0.0 config and test split of cnn_dailymail
#4 opened over 2 years ago
by
autoevaluator
Add evaluation results on the 3.0.0 config and test split of cnn_dailymail
#3 opened over 2 years ago
by
autoevaluator
Adding `safetensors` variant of this model
#2 opened almost 3 years ago
by
SFconvertbot
Can I check how many epochs this was finetuned on CNN for?
#1 opened over 3 years ago
by
magmarage