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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09e5922026867ba025fa652998a5a857091e8c98db1db82592d354f4c469f3d9
- Size of remote file:
- 4.16 kB
- SHA256:
- 4412b30bc9686f1ac865ac48ade8e0cddec099eb12cb6df9ccd9ad9c0bfcc96b
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