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  # Red Pajama's High Quality Spanish subset
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  The following is a high-quality dataset distilled from the Spanish subsection of [RedPajama-Data-v2](https://github.com/togethercomputer/RedPajama-Data), created using the methodology proposed for [FineWEB-Edu](https://arxiv.org/abs/2406.17557).
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  In a nutshell, we use Llama-3.1-70B to grade the educational quality of various samples from the original dataset. Then, we used these 500K samples to train a classifier using an encoder-based model, so that it learns to assign a score from 0 to 5. Since this model is way cheaper to use than an LLM, we run it over the entire dataset, thus getting a high-quality section from it.
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  Here is an overview of the architecture:
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b15c3f20037ec5d7c91aa6/H5xPOHy_4RhMEDtGvsnTE.png)
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  For more detailed information on how this dataset was created, refer to [our implementation](https://github.com/latam-gpt/llm-data-eval).
 
 
 
 
 
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  # Red Pajama's High Quality Spanish subset
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+ ## What is this?
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  The following is a high-quality dataset distilled from the Spanish subsection of [RedPajama-Data-v2](https://github.com/togethercomputer/RedPajama-Data), created using the methodology proposed for [FineWEB-Edu](https://arxiv.org/abs/2406.17557).
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+ ## Dataset creation
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  In a nutshell, we use Llama-3.1-70B to grade the educational quality of various samples from the original dataset. Then, we used these 500K samples to train a classifier using an encoder-based model, so that it learns to assign a score from 0 to 5. Since this model is way cheaper to use than an LLM, we run it over the entire dataset, thus getting a high-quality section from it.
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  Here is an overview of the architecture:
 
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b15c3f20037ec5d7c91aa6/H5xPOHy_4RhMEDtGvsnTE.png)
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  For more detailed information on how this dataset was created, refer to [our implementation](https://github.com/latam-gpt/llm-data-eval).
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+ ## License
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+ Please refer to the [Common Crawl Foundation Terms of Use](https://commoncrawl.org/terms-of-use) for the data. The code used to load and process the dataset is licensed under the Apache 2.0 license.