Instructions to use SEBIS/code_trans_t5_large_code_documentation_generation_java_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_java_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_java_multitask")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d8f0545dea7f61d2ca58f63793856c4695fe559d24f698a6046c35095b4189d
- Size of remote file:
- 2.95 GB
- SHA256:
- aaeffb1b6aeddafbed069e63e8ac4afbc57ba3ca6b3189dff45b1e253de84e86
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