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z-dickson
/
CAP_multilingual

Text Classification
Transformers
PyTorch
bert
CAP
politics
issues
agenda
multilingual
science
comparative agendas project
text-embeddings-inference
Model card Files Files and versions
xet
Community
5

Instructions to use z-dickson/CAP_multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use z-dickson/CAP_multilingual with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="z-dickson/CAP_multilingual")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("z-dickson/CAP_multilingual")
    model = AutoModelForSequenceClassification.from_pretrained("z-dickson/CAP_multilingual")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#5 opened 1 day ago by
SFconvertbot

Adding `safetensors` variant of this model

#4 opened 5 months ago by
SFconvertbot

Adding `safetensors` variant of this model

#3 opened 11 months ago by
SFconvertbot

Adding `safetensors` variant of this model

#2 opened 11 months ago by
SFconvertbot

Adding `safetensors` variant of this model

#1 opened over 1 year ago by
SFconvertbot
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