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almanach
/
camembertav2-base-cls

Text Classification
Transformers
TensorBoard
Safetensors
French
deberta-v2
review-classification
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use almanach/camembertav2-base-cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use almanach/camembertav2-base-cls with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="almanach/camembertav2-base-cls")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("almanach/camembertav2-base-cls")
    model = AutoModelForSequenceClassification.from_pretrained("almanach/camembertav2-base-cls", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
camembertav2-base-cls
446 MB
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  • 1 contributor
History: 2 commits
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wissamantoun
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  • logs
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  • .gitattributes
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  • README.md
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  • all_results.json
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  • config.json
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  • eval_results.json
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  • model.safetensors
    445 MB
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  • special_tokens_map.json
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  • tokenizer.json
    756 kB
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  • tokenizer_config.json
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  • train_results.json
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  • trainer_state.json
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  • training_args.bin
    5.56 kB
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  • vocab.txt
    235 kB
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