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huggingface
/
funnel-small-base

Feature Extraction
Transformers
PyTorch
funnel
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use huggingface/funnel-small-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="huggingface/funnel-small-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("huggingface/funnel-small-base")
    model = AutoModel.from_pretrained("huggingface/funnel-small-base")
  • Notebooks
  • Google Colab
  • Kaggle
funnel-small-base
925 MB
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History: 7 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
baaaa6b verified about 1 year ago
  • .gitattributes
    399 Bytes
    Adding `safetensors` variant of this model about 1 year ago
  • config.json
    599 Bytes
    Update config.json over 5 years ago
  • model.safetensors
    462 MB
    xet
    Adding `safetensors` variant of this model about 1 year ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch.FloatStorage",
    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    463 MB
    xet
    Update pytorch_model.bin over 5 years ago
  • special_tokens_map.json
    153 Bytes
    Update special_tokens_map.json over 5 years ago
  • tokenizer_config.json
    48 Bytes
    Update tokenizer_config.json over 5 years ago
  • vocab.txt
    231 kB
    Update vocab.txt over 5 years ago