Instructions to use FacebookAI/xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-roberta-base") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-roberta-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Add TF weights
#2
by joaogante - opened
Validated by the pt_to_tf CLI. Max crossload hidden state difference=8.106e-06; Max converted hidden state difference=8.106e-06.
joaogante changed pull request status to merged
(merging as we are the org in charge of this model)
fusion