Instructions to use SEBIS/code_trans_t5_large_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_large_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_large_api_generation_multitask_finetune")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_large_api_generation_multitask_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_large_api_generation_multitask_finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06237d38e2b2c64e5663a5d311a95f645207e336b400cc45ca7bd0aaec16da76
- Size of remote file:
- 2.95 GB
- SHA256:
- eedd8f26ba08a0a8620c74b72f6712aeb287f69f6577a9f41abaf9a41a8cab82
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