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bertin-project
/
bertin-base-random-exp-512seqlen

Fill-Mask
Transformers
PyTorch
JAX
TensorBoard
Joblib
Safetensors
Spanish
roberta
spanish
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Instructions to use bertin-project/bertin-base-random-exp-512seqlen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bertin-project/bertin-base-random-exp-512seqlen with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="bertin-project/bertin-base-random-exp-512seqlen")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-base-random-exp-512seqlen")
    model = AutoModelForMaskedLM.from_pretrained("bertin-project/bertin-base-random-exp-512seqlen")
  • Notebooks
  • Google Colab
  • Kaggle
bertin-base-random-exp-512seqlen / mc4
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  • 4 contributors
History: 1 commit

This model has 1 file scanned as suspicious.

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Step... (240001/250000 | Loss: 2.1932833194732666, Acc: 0.5893170833587646): 4%|▉ | 10063/250000 [3:28:31<88:33:32, 1.33s/it]
c725c08 almost 5 years ago
  • dummy
    Step... (240001/250000 | Loss: 2.1932833194732666, Acc: 0.5893170833587646): 4%|▉ | 10063/250000 [3:28:31<88:33:32, 1.33s/it] almost 5 years ago
  • README.md
    15.5 kB
    Step... (240001/250000 | Loss: 2.1932833194732666, Acc: 0.5893170833587646): 4%|▉ | 10063/250000 [3:28:31<88:33:32, 1.33s/it] almost 5 years ago
  • mc4.py
    14.1 kB
    Step... (240001/250000 | Loss: 2.1932833194732666, Acc: 0.5893170833587646): 4%|▉ | 10063/250000 [3:28:31<88:33:32, 1.33s/it] almost 5 years ago
  • mc4.py.lock
    0 Bytes
    Step... (240001/250000 | Loss: 2.1932833194732666, Acc: 0.5893170833587646): 4%|▉ | 10063/250000 [3:28:31<88:33:32, 1.33s/it] almost 5 years ago