Instructions to use SEBIS/code_trans_t5_small_api_generation_multitask_finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_small_api_generation_multitask_finetune 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_api_generation_multitask_finetune")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_small_api_generation_multitask_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_small_api_generation_multitask_finetune") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22aeb8a6d7a9edcd36eea0b81f6dfb69ccec79812a8cec92bcdd652a41b1f916
- Size of remote file:
- 242 MB
- SHA256:
- 0a3c39f7725efad26831952ad3268cc5ef26726633a4230ad0800e2268f1bbf0
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