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blackbird
/
bert-base-uncased-MNLI-v1

Text Classification
Transformers
PyTorch
JAX
Safetensors
bert
Model card Files Files and versions
xet
Community
1

Instructions to use blackbird/bert-base-uncased-MNLI-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use blackbird/bert-base-uncased-MNLI-v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="blackbird/bert-base-uncased-MNLI-v1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("blackbird/bert-base-uncased-MNLI-v1")
    model = AutoModelForSequenceClassification.from_pretrained("blackbird/bert-base-uncased-MNLI-v1")
  • Notebooks
  • Google Colab
  • Kaggle
bert-base-uncased-MNLI-v1
1.31 GB
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  • 4 contributors
History: 8 commits
blackbird's picture
blackbird
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#1)
f5131bf about 3 years ago
  • .gitattributes
    790 Bytes
    Adding `safetensors` variant of this model (#1) about 3 years ago
  • README.md
    118 Bytes
    Update README.md about 5 years ago
  • config.json
    773 Bytes
    Update from blackbird about 5 years ago
  • flax_model.msgpack
    438 MB
    xet
    upload flax model about 5 years ago
  • model.safetensors
    438 MB
    xet
    Adding `safetensors` variant of this model (#1) about 3 years ago
  • pytorch_model.bin
    438 MB
    xet
    Update from blackbird about 5 years ago
  • special_tokens_map.json
    112 Bytes
    Update from blackbird about 5 years ago
  • tokenizer_config.json
    285 Bytes
    Update from blackbird about 5 years ago
  • vocab.txt
    232 kB
    Update from blackbird about 5 years ago