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:
- 1f2b949f7b316dd0910e92910a1266bca4fdb24fcda6a151b34e7513740d076e
- Size of remote file:
- 17.1 MB
- SHA256:
- 2352cd7adf38fda759d5bfdfc88afe28fc328dc7d1ad511e5ee4d241b22ac6fa
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