Datasets:
Tasks:
Sentence Similarity
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10M - 100M
License:
Create README.md
Browse files
README.md
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Created vector embeddings for the `abstract` field for the dataset: [bluuebunny/crossref_metadata_2025_split](https://huggingface.co/datasets/bluuebunny/crossref_metadata_2025_split) using [mixedbread-ai/mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) and binarised it using:
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```python
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# Function to binarise float embeddings
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def binarise(row):
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# Make it a numpy array, since batching sends it as list
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float_vector = np.array(row['vector'], dtype=np.float32)
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# Binarise
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binary_vector = np.where(float_vector >= 0, 1, 0)
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# Pack it to make it milvus compatible
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row['vector'] = np.packbits(binary_vector).tobytes()
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return row
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```
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