Summarization
Transformers
PyTorch
TensorBoard
Safetensors
bart
text2text-generation
politics
climate change
political party
press release
political communication
European Union
Speech
Instructions to use z-dickson/bart-large-cnn-climate-change-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use z-dickson/bart-large-cnn-climate-change-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="z-dickson/bart-large-cnn-climate-change-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("z-dickson/bart-large-cnn-climate-change-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("z-dickson/bart-large-cnn-climate-change-summarization") - Notebooks
- Google Colab
- Kaggle
Training Data
#39
by kreabs - opened
Is there a way you can make your training data accessible as a hugging face dataset?
There is just not many datasets for training models for non-English-summarization .It would be great, if there is another dataset.
Greedings
kraebs
Hi Kraebs,
Thanks for getting in touch. There's currently an academic paper associated with the model that is under review. As soon as the paper is accepted, I'll upload the full dataset.
Thanks,
Zach
Thank you so much Zach!
All the best!