Instructions to use facebook/mbart-large-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mbart-large-50 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("facebook/mbart-large-50") model = AutoModelForSeq2SeqLM.from_pretrained("facebook/mbart-large-50") - Notebooks
- Google Colab
- Kaggle
Add TF weights
#6
by joaogante - opened
Model converted by the transformers' pt_to_tf CLI. All converted model outputs and hidden layers were validated against its PyTorch counterpart.
Maximum crossload output difference=2.670e-05; Maximum crossload hidden layer difference=9.766e-04;
Maximum conversion output difference=2.670e-05; Maximum conversion hidden layer difference=9.766e-04;
CAUTION: The maximum admissible error was manually increased to 0.001!
joaogante changed pull request status to merged