Instructions to use JoaoJunior/codet5-small-code-summarization-ruby-personal-learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JoaoJunior/codet5-small-code-summarization-ruby-personal-learning with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("JoaoJunior/codet5-small-code-summarization-ruby-personal-learning") model = AutoModelForSeq2SeqLM.from_pretrained("JoaoJunior/codet5-small-code-summarization-ruby-personal-learning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 825ab6c5378c400ce75ec3a1860cb3cd66d755ef4cce6de2f45971a342fac9f0
- Size of remote file:
- 242 MB
- SHA256:
- 48ed8f328506ad6f6d93f4824ac5136fd883f6525f8b1ba9973a312711e754ac
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