Instructions to use SEBIS/code_trans_t5_large_code_comment_generation_java_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_large_code_comment_generation_java_transfer_learning_finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SEBIS/code_trans_t5_large_code_comment_generation_java_transfer_learning_finetune")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_large_code_comment_generation_java_transfer_learning_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_large_code_comment_generation_java_transfer_learning_finetune") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#4 opened almost 3 years ago
by
SFconvertbot
model documentation
3
#3 opened over 3 years ago
by
nazneen
Upload README.md with huggingface_hub
#1 opened over 3 years ago
by
lbourdois