Instructions to use burcusu/ct2-codet5p-220m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use burcusu/ct2-codet5p-220m with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("burcusu/ct2-codet5p-220m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Quantized version of Salesforce/codet5p-220m
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# Licence and other remarks:
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Quantized version of Salesforce/codet5p-220m
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!ct2-transformers-converter --model Salesforce/codet5p-220m --output_dir /content/sample_data/codet5p-220m-ct2 --force --copy_files merges.txt README.md tokenizer_config.json vocab.json special_tokens_map.json added_tokens.json .gitattributes --quantization float16
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# Licence and other remarks:
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