Instructions to use SEBIS/code_trans_t5_base_code_documentation_generation_javascript_transfer_learning_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_code_documentation_generation_javascript_transfer_learning_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_code_documentation_generation_javascript_transfer_learning_finetune")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_base_code_documentation_generation_javascript_transfer_learning_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_base_code_documentation_generation_javascript_transfer_learning_finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload README.md with huggingface_hub
3c12c8e
-
upload flax model
cb90c96 -
allow flax
0b71e12
-
Update README.md
aa5ef6c
-
Update from weiding
wei946e66f -
initial commit
ef1b5a1