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README.md
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As an autoregressive language model, CodeGen2.5 is capable of extracting features from given natural language and programming language texts, and calculating the likelihood of them.
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However, the model is intended for and best at **program synthesis**, that is, generating executable code given English prompts, where the prompts should be in the form of a comment string. The model can complete partially-generated code as well.
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## BibTeX entry and citation info
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Please cite CodeGen2 paper:
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As an autoregressive language model, CodeGen2.5 is capable of extracting features from given natural language and programming language texts, and calculating the likelihood of them.
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However, the model is intended for and best at **program synthesis**, that is, generating executable code given English prompts, where the prompts should be in the form of a comment string. The model can complete partially-generated code as well.
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## Attribution & Other Requirements
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The pretraining dataset of the model was filtered for permissive licenses only.
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Nevertheless, the model can generate source code verbatim from the dataset.
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The code's license might require attribution and/or other specific requirements that must be respected.
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The data provider BigCode provides a [search index](https://huggingface.co/spaces/bigcode/starcoder-search) that lets you search through the pretraining data to identify where generated code came from and apply the proper attribution to your code.
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## BibTeX entry and citation info
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Please cite CodeGen2 paper:
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