Instructions to use Jinendra/code-t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jinendra/code-t5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Jinendra/code-t5") model = AutoModelForSeq2SeqLM.from_pretrained("Jinendra/code-t5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9017c157350b77f45a1eea78e369732d5b46a8f43ce40c402279127aa208338a
- Size of remote file:
- 446 MB
- SHA256:
- 494de3467719e2a95cc7bbd5988d0a405f71bb358e42cf7315a57171944f1ff2
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