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padmajabfrl
/
Religion-Classification-Custom-Model

Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
9

Instructions to use padmajabfrl/Religion-Classification-Custom-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use padmajabfrl/Religion-Classification-Custom-Model with Transformers:

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

Training dataset

1
#9 opened 5 months ago by
josejhlee

Librarian Bot: Add base_model information to model

#8 opened over 2 years ago by
librarian-bot

Adding `safetensors` variant of this model

#7 opened over 2 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#6 opened over 2 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#5 opened almost 3 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#4 opened almost 3 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#3 opened almost 3 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#2 opened almost 3 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#1 opened almost 3 years ago by
SFconvertbot
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