Instructions to use SEBIS/code_trans_t5_base_transfer_learning_pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_base_transfer_learning_pretrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SEBIS/code_trans_t5_base_transfer_learning_pretrain")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_base_transfer_learning_pretrain") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_base_transfer_learning_pretrain") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1315be320d7f0b96329a52db868d2273ccbbe40283bba03c71264e00e5a7fdbc
- Size of remote file:
- 892 MB
- SHA256:
- 95b87d6c0112b74d7bb95eb472b30ed4e041e720bd7cf0c403eddf33eaca13e2
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