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AmrSheta
/
Meme

Text Classification
Transformers
PyTorch
bert
feature-extraction
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use AmrSheta/Meme with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="AmrSheta/Meme")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("AmrSheta/Meme")
    model = AutoModel.from_pretrained("AmrSheta/Meme")
  • Notebooks
  • Google Colab
  • Kaggle
Meme
Ctrl+K
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  • 1 contributor
History: 18 commits
AmrSheta's picture
AmrSheta
Delete tokenizer.json
ab6b8aa about 4 years ago
  • .gitattributes
    1.18 kB
    initial commit about 4 years ago
  • Data_Scrapping.ipynb
    6.62 kB
    nlp model with tranformers about 4 years ago
  • Meme_Transformer1.ipynb
    489 kB
    nlp model with tranformers about 4 years ago
  • README.md
    69 Bytes
    Update README.md about 4 years ago
  • cleaning_and_conversion.ipynb
    6.83 kB
    nlp model with tranformers about 4 years ago
  • config.json
    656 Bytes
    add model about 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    433 MB
    xet
    add model about 4 years ago
  • read.txt
    115 Bytes
    nlp model with tranformers about 4 years ago