Instructions to use SEBIS/code_trans_t5_small_code_comment_generation_java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_small_code_comment_generation_java 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_small_code_comment_generation_java")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_small_code_comment_generation_java") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_small_code_comment_generation_java", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4581dc99d0bef1f5224501f2f8208caff352124a08fc5a18ce41e09f08febb6e
- Size of remote file:
- 242 MB
- SHA256:
- fa0d5fb29b3b41039367cf147e28d183295c0d3afe9b171b79e8b138d0bd1da8
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