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smeoni
/
apericube

Feature Extraction
Transformers
PyTorch
roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use smeoni/apericube with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use smeoni/apericube with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="smeoni/apericube")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("smeoni/apericube")
    model = AutoModel.from_pretrained("smeoni/apericube")
  • Notebooks
  • Google Colab
  • Kaggle
apericube
4.95 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
smeoni's picture
smeoni
add tokenizer
bbafbad almost 4 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • config.json
    650 Bytes
    add model almost 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    1.71 MB
    xet
    add model almost 4 years ago
  • sentencepiece.bpe.model
    811 kB
    xet
    add tokenizer almost 4 years ago
  • special_tokens_map.json
    354 Bytes
    add tokenizer almost 4 years ago
  • tokenizer.json
    2.42 MB
    add tokenizer almost 4 years ago
  • tokenizer_config.json
    522 Bytes
    add tokenizer almost 4 years ago