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
Commit ·
d8def28
1
Parent(s): 4082511
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:95b87d6c0112b74d7bb95eb472b30ed4e041e720bd7cf0c403eddf33eaca13e2
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size 891625348
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