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0x7o
/
rubert-base-massive

Text Classification
Transformers
PyTorch
ONNX
Safetensors
Russian
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use 0x7o/rubert-base-massive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use 0x7o/rubert-base-massive with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="0x7o/rubert-base-massive")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("0x7o/rubert-base-massive")
    model = AutoModelForSequenceClassification.from_pretrained("0x7o/rubert-base-massive")
  • Notebooks
  • Google Colab
  • Kaggle
rubert-base-massive
Ctrl+K
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  • 4 contributors
History: 10 commits
0x7o
Upload model.onnx
7d69dbb over 2 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    316 Bytes
    Update README.md over 3 years ago
  • config.json
    4.11 kB
    Update config.json over 3 years ago
  • model.onnx
    714 MB
    xet
    Upload model.onnx over 2 years ago
  • model.safetensors
    713 MB
    xet
    Adding `safetensors` variant of this model (#1) almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    713 MB
    xet
    First model version over 3 years ago
  • special_tokens_map.json
    125 Bytes
    First model version over 3 years ago
  • tokenizer.json
    3.71 MB
    First model version over 3 years ago
  • tokenizer_config.json
    379 Bytes
    First model version over 3 years ago
  • vocab.txt
    1.78 MB
    First model version over 3 years ago