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arbazk
/
maestroqa-distilbert-negative-sentiment

Text Classification
Transformers
PyTorch
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use arbazk/maestroqa-distilbert-negative-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use arbazk/maestroqa-distilbert-negative-sentiment with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="arbazk/maestroqa-distilbert-negative-sentiment")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("arbazk/maestroqa-distilbert-negative-sentiment")
    model = AutoModelForSequenceClassification.from_pretrained("arbazk/maestroqa-distilbert-negative-sentiment")
  • Notebooks
  • Google Colab
  • Kaggle

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Preview of files found in this repository
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • .gitignore
    13 Bytes
    Training in progress, epoch 1 about 3 years ago
  • README.md
    1.67 kB
    Update README.md about 3 years ago
  • config.json
    812 Bytes
    Training in progress, epoch 1 about 3 years ago
  • model.safetensors
    268 MB
    xet
    Adding `safetensors` variant of this model (#1) about 3 years ago
  • pytorch_model.bin
    268 MB
    xet
    Training in progress, epoch 4 about 3 years ago
  • special_tokens_map.json
    125 Bytes
    Training in progress, epoch 1 about 3 years ago
  • tokenizer.json
    711 kB
    Training in progress, epoch 1 about 3 years ago
  • tokenizer_config.json
    436 Bytes
    Training in progress, epoch 1 about 3 years ago
  • training_args.bin
    3.52 kB
    xet
    Training in progress, epoch 1 about 3 years ago
  • vocab.txt
    232 kB
    Training in progress, epoch 1 about 3 years ago