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High-level review (#2)
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[InCoder](https://huggingface.co/facebook/incoder-6B) is a code generation model that also allows code editing via [infilling](https://arxiv.org/pdf/2204.05999.pdf). It was trained on **216 GB** of preprocessed data from GitHub and Stack Overflow from 28 programming languages. 52 GB is in Python, 107GB in other programming languages and 57GB is content from Stackoverflow that isn't code.
The GitHub data was cleaned with the following steps:
- Average line length < 100 tokens
- Maximum line length < 3000 MB
- Alphanumeric characters fraction > 0.4
- Remove auto-generated files (keyword search)
The second component of the data consists of questions, answers, and comments from Stack Overflow. It includes:
- all questions that have at least one answer
- up to ten answers with a non-negative score (sorted by score) per question
- up to five comments per question/answer
Exact match deduplication was performed on code files. For more details please refer to this [paper](https://arxiv.org/pdf/2204.05999.pdf).