Instructions to use SEBIS/code_trans_t5_large_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_large_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_large_transfer_learning_pretrain")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_large_transfer_learning_pretrain") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_large_transfer_learning_pretrain") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c702be748c810701eb7723000771ee2a460d635c1badc1b284e4e201d95e927b
- Size of remote file:
- 2.95 GB
- SHA256:
- d09ecf8927670c7b76bfc5d33d93d8982803333f8d52e21c44f9120cc1ad8286
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