Instructions to use SEBIS/code_trans_t5_base_code_documentation_generation_go with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_base_code_documentation_generation_go 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_base_code_documentation_generation_go")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_base_code_documentation_generation_go") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_base_code_documentation_generation_go") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41348cb807c7d85f167deb0a5d634f6c78c581b24b19b18b953a3104cc5d9f23
- Size of remote file:
- 892 MB
- SHA256:
- f38a1d16ad5eeaa2a28da0bafc13c40ad0127ced3d50c92f3a0cb94be7699333
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.