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KBLab
/
megatron.bert-base.wordpiece-64k-pretok.25k-steps

Feature Extraction
Transformers
Safetensors
Swedish
megatron-bert
Model card Files Files and versions
xet
Community

Instructions to use KBLab/megatron.bert-base.wordpiece-64k-pretok.25k-steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use KBLab/megatron.bert-base.wordpiece-64k-pretok.25k-steps with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="KBLab/megatron.bert-base.wordpiece-64k-pretok.25k-steps")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("KBLab/megatron.bert-base.wordpiece-64k-pretok.25k-steps")
    model = AutoModel.from_pretrained("KBLab/megatron.bert-base.wordpiece-64k-pretok.25k-steps")
  • Notebooks
  • Google Colab
  • Kaggle
megatron.bert-base.wordpiece-64k-pretok.25k-steps
542 MB
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  • 1 contributor
History: 5 commits
robinq's picture
robinq
Upload nemo_train_params.yaml with huggingface_hub
abafe88 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    3.36 kB
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  • config.json
    642 Bytes
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  • model.safetensors
    541 MB
    xet
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  • nemo_train_params.yaml
    2.62 kB
    Upload nemo_train_params.yaml with huggingface_hub about 2 years ago
  • special_tokens_map.json
    971 Bytes
    Upload tokenizer about 2 years ago
  • tokenizer.json
    1.5 MB
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  • tokenizer_config.json
    1.16 kB
    Upload tokenizer about 2 years ago