Instructions to use SEBIS/code_trans_t5_large_source_code_summarization_sql_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_source_code_summarization_sql_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_source_code_summarization_sql_multitask_finetune")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_large_source_code_summarization_sql_multitask_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_large_source_code_summarization_sql_multitask_finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
upload flax model
e9ee947 -
allow flax
2ed636f
-
Update README.md
2c0dfae
-
Update from weiding
wei791d242 -
initial commit
22937ee