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/README.md:
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 1 | # Papers with code datasets
 2 | 
 3 | You can download the full dataset behind [paperswithcode.com](https://paperswithcode.com) here:
 4 | 
 5 | Download links for the data dumps are:
 6 | 
 7 | - [All papers with abstracts](https://production-media.paperswithcode.com/about/papers-with-abstracts.json.gz)
 8 | - [Links between papers and code](https://production-media.paperswithcode.com/about/links-between-papers-and-code.json.gz)
 9 | - [Evaluation tables](https://production-media.paperswithcode.com/about/evaluation-tables.json.gz)
10 | - [Methods](https://production-media.paperswithcode.com/about/methods.json.gz)
11 | - [Datasets](https://production-media.paperswithcode.com/about/datasets.json.gz)
12 | 
13 | The last JSON is in the [sota-extractor](https://github.com/paperswithcode/sota-extractor) format and the code
14 | from there can be used to load in the JSON into a set of Python classes. 
15 | 
16 | At the moment, data is regenerated daily.
17 | 
18 | Part of the data is coming from the sources listed in the [sota-extractor README](https://github.com/paperswithcode/sota-extractor).
19 | 
20 | ## Licence
21 | 
22 | All data is licenced under [CC-BY-SA](https://creativecommons.org/licenses/by-sa/4.0/). 
23 | 
24 | 
25 | 


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