Instructions to use SEBIS/code_trans_t5_small_source_code_summarization_csharp_multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_small_source_code_summarization_csharp_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_small_source_code_summarization_csharp_multitask")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_small_source_code_summarization_csharp_multitask") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_small_source_code_summarization_csharp_multitask") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ab3cb6b546ccc1d09b743deecf7968be837b109a910a1ef16dbe85518b30274
- Size of remote file:
- 242 MB
- SHA256:
- 255e00eef8fb7997f15cf2ad33aafae16617ee47388403a2661b770e5568c568
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