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FacebookAI
/
xlm-roberta-base

Fill-Mask
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
ONNX
Safetensors
xlm-roberta
exbert
Model card Files Files and versions
xet
Community
28

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
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Multilingual powerhouse — testing for mobile deployment

#30 opened 2 days ago by
3morixd

TemporalMesh Transformer: 29.4 PPL at 48% compute — beats Mamba, new open-source architecture

#29 opened 21 days ago by
vigneshwar234

Tokenizer vocabulary

#28 opened almost 2 years ago by
DjTobalito

Inquiry about Batch Size and Total Steps Used for MLM Task on xlm-roberta?

1
#26 opened over 2 years ago by
jrjrjrjr

Cosine Similarity is very high with Japanese Sentences

4
#18 opened about 3 years ago by
Kizaburo

Multi-Label Support?

#17 opened about 3 years ago by
hanshupe

Request: DOI

1
#12 opened over 3 years ago by
Hallgeir

Update README.md

#8 opened over 3 years ago by deleted

Update README.md

#7 opened over 3 years ago by deleted
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