Instructions to use SEBIS/code_trans_t5_small_program_synthese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_small_program_synthese 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_program_synthese")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_small_program_synthese") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_small_program_synthese") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35c25cbbff47824bed93f8faf451ab7b80427c4c41df063bd7c29936ed26e55e
- Size of remote file:
- 242 MB
- SHA256:
- 2a79a6a6d43bc0b77a9916b5a4c5759e4ae65d5a72ad2e6a3532393dc66ad48b
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