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IIIT-L
/
albert-base-v2-finetuned-non-code-mixed-DS

Text Classification
Transformers
PyTorch
albert
Generated from Trainer
Model card Files Files and versions
xet
Community
1

Instructions to use IIIT-L/albert-base-v2-finetuned-non-code-mixed-DS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use IIIT-L/albert-base-v2-finetuned-non-code-mixed-DS with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="IIIT-L/albert-base-v2-finetuned-non-code-mixed-DS")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("IIIT-L/albert-base-v2-finetuned-non-code-mixed-DS")
    model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/albert-base-v2-finetuned-non-code-mixed-DS")
  • Notebooks
  • Google Colab
  • Kaggle
albert-base-v2-finetuned-non-code-mixed-DS
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  • 1 contributor
History: 3 commits
Nazia Nafis
update model card README.md
d33b24f over 3 years ago
  • .gitattributes
    1.38 kB
    initial commit over 3 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 926 over 3 years ago
  • README.md
    1.55 kB
    update model card README.md over 3 years ago
  • config.json
    1.04 kB
    Training in progress, step 926 over 3 years ago
  • pytorch_model.bin
    46.8 MB
    xet
    Training in progress, step 926 over 3 years ago
  • special_tokens_map.json
    286 Bytes
    Training in progress, step 926 over 3 years ago
  • tokenizer.json
    2.27 MB
    Training in progress, step 926 over 3 years ago
  • tokenizer_config.json
    526 Bytes
    Training in progress, step 926 over 3 years ago
  • training_args.bin
    3.38 kB
    xet
    Training in progress, step 926 over 3 years ago