Instructions to use DunnBC22/codet5-base-Generate_Docstrings_for_Python-Condensed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/codet5-base-Generate_Docstrings_for_Python-Condensed with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DunnBC22/codet5-base-Generate_Docstrings_for_Python-Condensed") model = AutoModelForSeq2SeqLM.from_pretrained("DunnBC22/codet5-base-Generate_Docstrings_for_Python-Condensed") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 533200f37269768b58b40c4bf1439b92e2bf5d1e6c67ce1a79945426952fb7b4
- Size of remote file:
- 892 MB
- SHA256:
- bd6203ae603abb7a42e060d2fda425d9fb8288c23e397756551a4a9b06b5cdfa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.