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:
- 50f316fd7d7a73e80ad8a05651a16367d183467110821d9157ddf49c6652de1a
- Size of remote file:
- 1.63 GB
- SHA256:
- cd613ef33367969b05c15ee8c72ef85f7ae28cf6d70375d668f8a2e70126c937
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