Transformers
Safetensors
Portuguese
bart
text2text-generation
text-summarization
abstractive-summarization
portuguese
administrative-documents
municipal-meetings
bart-large-cnn
Instructions to use anonymous12321/Bart-Large-Summarization-Council-PT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anonymous12321/Bart-Large-Summarization-Council-PT with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("anonymous12321/Bart-Large-Summarization-Council-PT") model = AutoModelForSeq2SeqLM.from_pretrained("anonymous12321/Bart-Large-Summarization-Council-PT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b574d32ea44d7ca0bc4adee7dbb9ec48b9a70021049b392b84aba210f1470410
- Size of remote file:
- 5.78 kB
- SHA256:
- 1c58dd2a5c30e4cbc9730abb5ca12257cf114ac10c5f1a7c44750bc6c3e67357
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.