Instructions to use Ransaka/mBart-en-sin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ransaka/mBart-en-sin with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ransaka/mBart-en-sin") model = AutoModelForSeq2SeqLM.from_pretrained("Ransaka/mBart-en-sin") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1513d72352c3cfd896800f674d2630f62e2fa7d0137f295538221f6dcb0ca00a
- Size of remote file:
- 5.3 kB
- SHA256:
- c964924c6af8ef407ca33d421593ed97d5f395bba641192567e226a6aedd3ea7
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