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VIITPune
/
praTran

Translation
Transformers
TensorBoard
Safetensors
m2m_100
text2text-generation
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use VIITPune/praTran with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use VIITPune/praTran with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "translation" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("translation", model="VIITPune/praTran")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("VIITPune/praTran")
    model = AutoModelForSeq2SeqLM.from_pretrained("VIITPune/praTran", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
praTran
1.94 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
sarch7040's picture
sarch7040
Duplicate from sarch7040/praTran
aa26857 verified almost 2 years ago
  • runs
    Duplicate from sarch7040/praTran almost 2 years ago
  • .gitattributes
    1.52 kB
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  • README.md
    2.2 kB
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  • added_tokens.json
    2.01 kB
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  • config.json
    935 Bytes
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  • generation_config.json
    198 Bytes
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  • model.safetensors
    1.94 GB
    xet
    Duplicate from sarch7040/praTran almost 2 years ago
  • prakrit_translation.csv
    354 kB
    Duplicate from sarch7040/praTran almost 2 years ago
  • sentencepiece.bpe.model
    2.42 MB
    xet
    Duplicate from sarch7040/praTran almost 2 years ago
  • special_tokens_map.json
    1.56 kB
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  • tokenizer_config.json
    19.8 kB
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  • training_args.bin
    5.37 kB
    xet
    Duplicate from sarch7040/praTran almost 2 years ago
  • vocab.json
    3.71 MB
    Duplicate from sarch7040/praTran almost 2 years ago