Instructions to use SEBIS/code_trans_t5_base_api_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_base_api_generation 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_api_generation")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_base_api_generation") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_base_api_generation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa7b3f93208ed4444cd755a5eaeedd4ea97cf74d531723f1a424b8806ef756e6
- Size of remote file:
- 892 MB
- SHA256:
- 0e7ea37c04978aa27025ca19efb4cce9689bddecb04923c61dd7c2205d65fd96
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