Instructions to use FacebookAI/xlm-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-roberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-roberta-large") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-roberta-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Add TF weights
Joao GanteAdds TF weights. Validated by the `pt_to_tf` CLI: crossload_diff=2.956390380859375e-05, converted_diff=2.956390380859375e-0569ec3f8
-
remove ipynb ckpt
6193590 -
add flax model
268a43b -
track msgpack
91703fe
-
Add model card
682e73b
-
Update tokenizer.json
208cd28
-
Update config.json
9b502fb
-
Update config.json
8820e13
-
Update sentencepiece.bpe.model
3622bd3 -
Update pytorch_model.bin
c8c5344 -
Update config.json
546d9eb -
initial commit
dba7212