Transformers
Safetensors
Portuguese
mbart
text2text-generation
text-summarization
title-generation
portuguese
administrative-documents
municipal-meetings
mbart-50
Instructions to use inesctec/CitiLink-mBART-50-Theme-Generation-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inesctec/CitiLink-mBART-50-Theme-Generation-pt with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("inesctec/CitiLink-mBART-50-Theme-Generation-pt") model = AutoModelForSeq2SeqLM.from_pretrained("inesctec/CitiLink-mBART-50-Theme-Generation-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c136bb967c83f94bf00a6b575d911b88a38a488fd0701f62f317097e34f794f
- Size of remote file:
- 2.44 GB
- SHA256:
- b89151a95287ac55ad222d258e1ee52e05a91d0f727aec29e7086586b2a656a5
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