feat(skeleton): READMEs

README.md

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+# sr-detection
+
+The goal of the study is to create a model that, by looking at the README file
+and meta-information, can identify GitHub ``sample repositories'' (SR), that
+mostly contain educational or demonstration materials supposed to be copied
+instead of reused as a dependency.
+
+**Motivation**. During the work on [CaM] project, we were required to
+[filter out repositories with samples][cam-issue]. No readily available
+technique or tool existed that could perform that function, so we conducted
+research on this very subject.
+
+The repository structured as follows:
+
+* [sr-data](/sr-data), module for collection, preprocessing and preparing the
+SR data.
+* [sr-train](/sr-train), module for training ML models.
+* [sr-detector](sr-detector), trained and reusable model for SR detection.
+* [sr-paper](/sr-paper), LaTeX source for a paper on SR detection.
+
+## How to contribute
+
+It's a Python project, so make sure that you have [Python 3.11+] on your
+system, fork this repository, make changes, send us a [pull request][guidelines].
+We will review your changes and apply them to the `master` branch shortly,
+provided they don't violate our quality standards. To avoid frustration, before
+sending us your pull request please run full build:
+
+```bash
+poetry build
+```
+
+[CaM]: https://github.com/yegor256/cam
+[cam-issue]: https://github.com/yegor256/cam/issues/227
+[guidelines]: https://www.yegor256.com/2014/04/15/github-guidelines.html
+[Python 3.11+]: https://www.python.org/downloads/release/python-3110

sr-paper/README.md

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+# paper
+
+[![latexmk](https://github.com/h1alexbel/sr-detection/actions/workflows/latexmk.yml/badge.svg)](https://github.com/h1alexbel/sr-detection/actions/workflows/latexmk.yml)
+
+This paper reveals samples-filter models performance and how they were trained.
+
+Auto-generated PDF is here: [paper.pdf](https://github.com/h1alexbel/sr-detection/blob/gh-pages/paper.pdf)
+
+To build a paper, run this:
+
+```bash
+latexmk paper.tex -pdf
+```
+
+Feel free to contribute, via pull requests.