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:
- d2602bc86dda41440c3b55cfe4b7b09b4e15c584b0d37a4ff61c3ce3e1c500fe
- Size of remote file:
- 242 MB
- SHA256:
- 8f5fd8989a5736d9e1beda343cd627070dd894f910869f7b396639d7a6d04667
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