Instructions to use raphaelmerx/xlm-roberta-large-tetun with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raphaelmerx/xlm-roberta-large-tetun with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="raphaelmerx/xlm-roberta-large-tetun")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("raphaelmerx/xlm-roberta-large-tetun") model = AutoModelForMaskedLM.from_pretrained("raphaelmerx/xlm-roberta-large-tetun") - Notebooks
- Google Colab
- Kaggle
Tetun BERT model
A fine-tune of xlm-roberta-large trained on Tetun data with a masked language modelling objective.
Tetun data used: MADLAD tet clean split (~40k documents).
Trained for 10 epochs with hyper params from the MasakhaNER paper (lr 5e-5 etc).
- Downloads last month
- 6