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README.md
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- n<1K
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`counts_and_indices.zip` contains all the result jsons (for the estimated frequencies for image-only, text-only and image-text searches) and the sample indices that are tagged to each concept for the LAION400m/LAION-Aesthetics datasets.
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For more details, see our [github repository](https://github.com/bethgelab/frequency_determines_performance)
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- n<1K
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**Frequency estimation results and tagged samples:** `counts_and_indices.zip` contains all the result jsons (for the estimated frequencies for image-only, text-only and image-text searches) and the sample indices that are tagged to each concept for the LAION400m/LAION-Aesthetics datasets.
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**Constructed dictionaries and other pretraining and downstream data artefacts:** Due to the large size of all our data artefacts, we release our dictionaries and other feature artefacts as split files of a 110GB sized zip file (named as `features_zip_part_aa`, `features_zip_part_ab` and `features_zip_part_ac`). Please download the individual split files, and then manually combine them to reconstruct the original zip file like this:
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```bash
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cat features_zip_part_aa features_zip_part_ab features_zip_part_ac > features.zip
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```
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Once combined, please verify that the file is correctly transferred by comparing the md5sum hash of the file:
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```bash
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md5sum features.zip
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```
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The output hash should be: `11f6339df3206257efdfc4a54dd7ca60 features.zip`
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For more details, see our [github repository](https://github.com/bethgelab/frequency_determines_performance)
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