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Tochka-AI
/
ruRoPEBert-e5-base-2k

Feature Extraction
Transformers
Safetensors
Russian
bert
fill-mask
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use Tochka-AI/ruRoPEBert-e5-base-2k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Tochka-AI/ruRoPEBert-e5-base-2k with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Tochka-AI/ruRoPEBert-e5-base-2k", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("Tochka-AI/ruRoPEBert-e5-base-2k", trust_remote_code=True)
    model = AutoModelForMaskedLM.from_pretrained("Tochka-AI/ruRoPEBert-e5-base-2k", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
ruRoPEBert-e5-base-2k
563 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
Tochka-AI's picture
Tochka-AI
Update README.md
2cb9947 verified about 2 years ago
  • .gitattributes
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  • README.md
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  • config.json
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  • generation_config.json
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  • model.safetensors
    556 MB
    xet
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  • modeling_rope_bert.py
    46.2 kB
    Added model code about 2 years ago
  • sentencepiece.bpe.model
    1.67 MB
    xet
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  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    4.92 MB
    xet
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  • tokenizer_config.json
    1.17 kB
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