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## Description
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This model is derived from [OpenCoder-1.5B-Base](https://huggingface.co/infly/OpenCoder-1.5B-Base) by applying an additional context extension fine-tuning with an Adjustment of the Base Frequency parameter of RoPE from 10,000 to 500,000. The number of optimization steps is 512 with a batch size of 128 on sequences of 16,384 length. The repository context is composed based on the _Path Distance_ heuristics, more details on which and other aspects including all code used can be found on the [Home Page](https://github.com/sapromak/adaptive-code-completion) of the project. Note that this model is created with the intent to answer specific research questions and __not__ to gain the maximum possible performance on the repository-level code completion setup. Consider it more as a baseline.
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The associated research was initialized and conducted by the [JetBrains Research](https://huggingface.co/JetBrains-Research) association.
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## Description
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This model is derived from [OpenCoder-1.5B-Base](https://huggingface.co/infly/OpenCoder-1.5B-Base) by applying an additional context extension fine-tuning with an Adjustment of the Base Frequency parameter of RoPE from 10,000 to 500,000. The number of optimization steps is 512 with a batch size of 128 on sequences of 16,384 length. The repository context is composed based on the _Path Distance_ heuristics, more details on which and other aspects, including all code used, can be found on the [Home Page](https://github.com/sapromak/adaptive-code-completion) of the project. Note that this model is created with the intent to answer specific research questions and __not__ to gain the maximum possible performance on the repository-level code completion setup. Consider it more as a baseline.
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The associated research was initialized and conducted by the [JetBrains Research](https://huggingface.co/JetBrains-Research) association.
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