---
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](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:
```python
# 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
```