Instructions to use SEBIS/code_trans_t5_base_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_base_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_base_api_generation_multitask_finetune")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_base_api_generation_multitask_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_base_api_generation_multitask_finetune") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d68b976dbdc0e3d52de3bd0e2d288bb7084dca7da41fdafa8ae2e91a41790256
- Size of remote file:
- 892 MB
- SHA256:
- a96887d65a24463241e9ce72a00703e9e548f6e72451028885d7aa28711056ae
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