README.md

metadata

license: apache-2.0
task_categories:
  - sentence-similarity
language:
  - en
tags:
  - doi
  - bibliography
  - literature
  - crossref
pretty_name: crossref 2025
size_categories:
  - 10M<n<100M

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