Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

shed-e
/
Translation

Translation
Transformers
PyTorch
TensorBoard
marian
text2text-generation
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
2

Instructions to use shed-e/Translation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use shed-e/Translation 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="shed-e/Translation")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("shed-e/Translation")
    model = AutoModelForSeq2SeqLM.from_pretrained("shed-e/Translation")
  • Notebooks
  • Google Colab
  • Kaggle
Translation / runs
16.7 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
shed-e's picture
shed-e
Training complete
942de75 over 3 years ago
  • Aug31_10-32-33_d03e85188e03
    Training complete over 3 years ago