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Haadini
/
xlm-base

Fill-Mask
Transformers
Safetensors
xlm-roberta
Model card Files Files and versions
xet
Community

Instructions to use Haadini/xlm-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Haadini/xlm-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="Haadini/xlm-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("Haadini/xlm-base")
    model = AutoModelForMaskedLM.from_pretrained("Haadini/xlm-base")
  • Notebooks
  • Google Colab
  • Kaggle
xlm-base
574 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Haadini's picture
Haadini
Best model: Epoch 1/3, Val Loss: 0.5597
79e9f70 verified 7 months ago
  • .gitattributes
    1.57 kB
    Best model: Epoch 1/3, Val Loss: 0.5597 7 months ago
  • README.md
    5.17 kB
    Best model: Epoch 1/3, Val Loss: 0.5597 7 months ago
  • config.json
    698 Bytes
    Best model: Epoch 1/3, Val Loss: 0.5597 7 months ago
  • model.safetensors
    557 MB
    xet
    Best model: Epoch 1/3, Val Loss: 0.5597 7 months ago
  • special_tokens_map.json
    280 Bytes
    Best model: Epoch 1/3, Val Loss: 0.5597 7 months ago
  • tokenizer.json
    17.1 MB
    xet
    Best model: Epoch 1/3, Val Loss: 0.5597 7 months ago
  • tokenizer_config.json
    1.21 kB
    Best model: Epoch 1/3, Val Loss: 0.5597 7 months ago