Instructions to use SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask 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_python_multitask 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_python_multitask")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask: direct link, hf CLI and curl.
- Browser
- Download file 178 Bytes
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https://huggingface.co/SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask/resolve/5d10070c28fd3049eef64f956142108139a62b99/README.md
- Command line
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hf download hf://SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask@5d10070c28fd3049eef64f956142108139a62b99/README.md
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curl -L -o README.md https://huggingface.co/SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask/resolve/5d10070c28fd3049eef64f956142108139a62b99/README.md
178 Bytes
metadata
tags:
- summarization
widget:
- text: >-
def e ( message , exit_code = None ) : print_log ( message , YELLOW , BOLD
) if exit_code is not None : sys . exit ( exit_code )