Instructions to use PHISSTOOD/codet5-small-code-summarization-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PHISSTOOD/codet5-small-code-summarization-python with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PHISSTOOD/codet5-small-code-summarization-python") model = AutoModelForSeq2SeqLM.from_pretrained("PHISSTOOD/codet5-small-code-summarization-python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00eb3962fe8f8bf96559dc21f52c0f3d99b0d3880934b1b0b47212e78e99379d
- Size of remote file:
- 242 MB
- SHA256:
- 3bfbfe5e7c8fd667ab34db70e0282a5b06f7a56205bd2022181ce86f28cc4765
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