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