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Apucs
/
bn_model_821k_iter_loss_1_24-finetuned-mnli-mm

Text Classification
Transformers
TensorBoard
Safetensors
bert
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use Apucs/bn_model_821k_iter_loss_1_24-finetuned-mnli-mm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Apucs/bn_model_821k_iter_loss_1_24-finetuned-mnli-mm with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Apucs/bn_model_821k_iter_loss_1_24-finetuned-mnli-mm")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Apucs/bn_model_821k_iter_loss_1_24-finetuned-mnli-mm")
    model = AutoModelForSequenceClassification.from_pretrained("Apucs/bn_model_821k_iter_loss_1_24-finetuned-mnli-mm", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
bn_model_821k_iter_loss_1_24-finetuned-mnli-mm / runs
24 kB
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  • 1 contributor
History: 1 commit
Apucs's picture
Apucs
Training in progress, epoch 1
0385647 almost 3 years ago
  • Nov10_12-24-34_092fb78c885e
    Training in progress, epoch 1 almost 3 years ago