Instructions to use DunnBC22/codet5-small-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-small-Generate_Docstrings_for_Python-Condensed with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DunnBC22/codet5-small-Generate_Docstrings_for_Python-Condensed") model = AutoModelForSeq2SeqLM.from_pretrained("DunnBC22/codet5-small-Generate_Docstrings_for_Python-Condensed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from DunnBC22/codet5-small-Generate_Docstrings_for_Python-Condensed: direct link, hf CLI and curl.
- Browser
- Download file 1.37 MB
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https://huggingface.co/DunnBC22/codet5-small-Generate_Docstrings_for_Python-Condensed/resolve/main/tokenizer.json
- Command line
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hf download hf://DunnBC22/codet5-small-Generate_Docstrings_for_Python-Condensed/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/DunnBC22/codet5-small-Generate_Docstrings_for_Python-Condensed/resolve/main/tokenizer.json
1.37 MB
File too large to display, you can check the raw version instead.