All Minilm L6 V2 With Attentions

🚀 ONNX Port of Sentence-Transformers Model for BM42 Searches

This project is an ONNX port of sentence-transformers/all-MiniLM-L6-v2, adjusted to return attention weights. It's designed for BM42 searches.

🚀 Quick Start

This model is an ONNX port of sentence-transformers/all-MiniLM-L6-v2 with adjustments to return attention weights. It's specifically tailored for BM42 searches.

💻 Usage Examples

Basic Usage

# Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed).
from fastembed import SparseTextEmbedding

documents = [
    "You should stay, study and sprint.",
    "History can only prepare us to be surprised yet again.",
]

model = SparseTextEmbedding(model_name="Qdrant/bm42-all-minilm-l6-v2-attentions")
embeddings = list(model.embed(documents))

# [
#     SparseEmbedding(values=array([0.26399775, 0.24662513, 0.47077307]),
#                     indices=array([1881538586, 150760872, 1932363795])),
#     SparseEmbedding(values=array(
#         [0.38320042, 0.25453135, 0.18017513, 0.30432631, 0.1373556]),
#                     indices=array([
#                         733618285, 1849833631, 1008800696, 2090661150,
#                         1117393019
#                     ]))
# ]

📄 License

This project is licensed under the Apache-2.0 license.