Instructions to use SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask 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_documentation_generation_python_multitask 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_code_documentation_generation_python_multitask")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask: direct link, hf CLI and curl.
- Browser
- Download file 797 kB
-
https://huggingface.co/SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask/resolve/refs%2Fpr%2F1/spiece.model
- Command line
-
hf download hf://SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask@refs/pr/1/spiece.model
-
curl -L -o spiece.model https://huggingface.co/SEBIS/code_trans_t5_large_code_documentation_generation_python_multitask/resolve/refs%2Fpr%2F1/spiece.model
797 kB
- Xet hash:
- b2c7e8ef85ff0ceab80b31d0b61ba60ad52ffa9b842b89c4bb91bcd6e03722d9
- Size of remote file:
- 797 kB
- SHA256:
- 9856b76e9978cc5805f0566cedabd2fc7bdb1a3ee22d52545100c056cb09a59c
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