Instructions to use dandrade/mbart-en-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dandrade/mbart-en-pt with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dandrade/mbart-en-pt") model = AutoModelForSeq2SeqLM.from_pretrained("dandrade/mbart-en-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dandrade/mbart-en-pt: direct link, hf CLI and curl.
- Browser
- Download file 2.44 GB
-
https://huggingface.co/dandrade/mbart-en-pt/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dandrade/mbart-en-pt/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dandrade/mbart-en-pt/resolve/main/pytorch_model.bin
2.44 GB
- Xet hash:
- 81b217459c40eceb8a8a4df736803e25a79c23093a4a607fe96b18965bf52ae7
- Size of remote file:
- 2.44 GB
- SHA256:
- aa2107f229b9a3dd99cbb9fcb4a7d47734a34bca4f3995f0b3beb5cc86ac5ad6
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