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leonas5555
/
finnews-topic-single-classify

Text Classification
Transformers
TensorBoard
Safetensors
PyTorch
bert
finance
financial-news
topic-classification
financial
news
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use leonas5555/finnews-topic-single-classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use leonas5555/finnews-topic-single-classify with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="leonas5555/finnews-topic-single-classify")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("leonas5555/finnews-topic-single-classify")
    model = AutoModelForSequenceClassification.from_pretrained("leonas5555/finnews-topic-single-classify")
  • Notebooks
  • Google Colab
  • Kaggle
finnews-topic-single-classify
440 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
leonas5555's picture
leonas5555
Update README.md
57c632a verified about 1 year ago
  • logs
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  • .gitattributes
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  • .gitignore
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  • README.md
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  • config.json
    1.82 kB
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  • model.safetensors
    439 MB
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.26 kB
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  • training_args.bin

    Detected Pickle imports (10)

    • "transformers.trainer_utils.HubStrategy",
    • "transformers.trainer_pt_utils.AcceleratorConfig",
    • "torch.device",
    • "transformers.training_args.TrainingArguments",
    • "accelerate.utils.dataclasses.DistributedType",
    • "transformers.trainer_utils.SaveStrategy",
    • "transformers.trainer_utils.SchedulerType",
    • "transformers.trainer_utils.IntervalStrategy",
    • "transformers.training_args.OptimizerNames",
    • "accelerate.state.PartialState"

    How to fix it?

    5.3 kB
    xet
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  • vocab.txt
    226 kB
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