Transformers
PyTorch
Safetensors
py
English
t5
text2text-generation
Code2TextGeneration
Code2TextSummarisation
text-generation-inference
Instructions to use stmnk/codet5-small-code-summarization-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stmnk/codet5-small-code-summarization-python with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("stmnk/codet5-small-code-summarization-python") model = AutoModelForSeq2SeqLM.from_pretrained("stmnk/codet5-small-code-summarization-python") - Notebooks
- Google Colab
- Kaggle
add link 2 report
Browse files
README.md
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See [this w&b report](https://wandb.ai/stmnk/CodeT5/reports/Code-T5-code_x_glue_code2text--VmlldzoxMjM4MTUy?accessToken=5stsbg6bn2x0m6svrosxtq0zv3vhlgzr4cjcyapw52xq5puc09wo6f8li40ln7fm) for fine-tuning metrics.
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<!-- <iframe src="https://wandb.ai/stmnk/CodeT5/reports/Code-T5-code_x_glue_code2text--VmlldzoxMjM4MTUy" style="border:none;height:1024px;width:100%"> -->
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