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Add centroids and README.md

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+ all_cluster_centroids_10000.json filter=lfs diff=lfs merge=lfs -text
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+ all_cluster_centroids_20000.json filter=lfs diff=lfs merge=lfs -text
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  license: apache-2.0
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  license: apache-2.0
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+ # Subjects-for-curricular
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+ ---
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+ Subjects-for-curricular is a clustered set of book titles and concepts from https://huggingface.co/datasets/benxh/opensyllabus-tagged-libgen and https://huggingface.co/datasets/benxh/us-library-of-congress-subjects.
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+ These two datasets are combined, taking the 'text' field from the US library of congress subjects (subjects_fixed.jsonl), and the 'name' field from the opensyllabus data. This text data is then converted into embeddings using the [bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) model.
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+ The embeddings are clustered into topics using K-means clustering. We include data for k=10,000 (all_topic_clusters_10000.parquet) and k=20,000 (all_topic_clusters_20000.parquet). We also include the centroid embeddings for each cluster. Both runs used 100 iterations of the k-means algorithm.
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