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voidful
/
albert_chinese_base

Fill-Mask
Transformers
PyTorch
Safetensors
Chinese
albert
Model card Files Files and versions
xet
Community
1

Instructions to use voidful/albert_chinese_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use voidful/albert_chinese_base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="voidful/albert_chinese_base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("voidful/albert_chinese_base")
    model = AutoModelForMaskedLM.from_pretrained("voidful/albert_chinese_base")
  • Notebooks
  • Google Colab
  • Kaggle
albert_chinese_base
85.5 MB
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  • 3 contributors
History: 10 commits
voidful's picture
voidful
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#1)
84609be about 3 years ago
  • .gitattributes
    399 Bytes
    Adding `safetensors` variant of this model (#1) about 3 years ago
  • README.md
    1.71 kB
    update readme almost 5 years ago
  • config.json
    704 Bytes
    update auto tokenizer support almost 5 years ago
  • model.safetensors
    42.7 MB
    xet
    Adding `safetensors` variant of this model (#1) about 3 years ago
  • pytorch_model.bin
    42.7 MB
    xet
    Update pytorch_model.bin about 6 years ago
  • special_tokens_map.json
    112 Bytes
    update auto tokenizer support almost 5 years ago
  • tokenizer_config.json
    378 Bytes
    update auto tokenizer support almost 5 years ago
  • vocab.txt
    110 kB
    Update vocab.txt about 6 years ago