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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d227cd4c09627cf7e66ede74927fba84ddae71c9300d240b4c4135aba1c478a2
- Size of remote file:
- 2.95 GB
- SHA256:
- 5fdcfd8ef1aa429e506e5b6100ffd218b71c780f949a64e8bf77de7618e775ef
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