Transformers
Safetensors
Portuguese
pegasus
text2text-generation
text-summarization
abstractive-summarization
portuguese
administrative-documents
municipal-meetings
Instructions to use anonymous12321/Pegasus-Summarization-Council-PT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anonymous12321/Pegasus-Summarization-Council-PT with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("anonymous12321/Pegasus-Summarization-Council-PT") model = AutoModelForSeq2SeqLM.from_pretrained("anonymous12321/Pegasus-Summarization-Council-PT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd0ad306cac5d658410f4687a2dd25bb856b54ccadde6c9379d7fbc50e5a5e5b
- Size of remote file:
- 5.78 kB
- SHA256:
- 1dc92cab208e76bdea3d12631efab03b8b7c60aedfb8956c80eb2bfdb3023ade
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.