Instructions to use SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask_finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask_finetune with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask_finetune")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask_finetune") - Notebooks
- Google Colab
- Kaggle
Commit ·
9f4f621
1
Parent(s): b453162
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 sha256:46d8fa6c704b01b74256a197f118a215fb83c42f25cb3c51e7b6e03eee5fcf1e
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size 2950694412
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