|
--- |
|
license: apache-2.0 |
|
pipeline_tag: sentence-similarity |
|
--- |
|
|
|
ONNX port of [prithivida/Splade_PP_en_v1](https://huggingface.co/prithivida/Splade_PP_en_v1) for text classification and similarity searches. |
|
|
|
### Usage |
|
|
|
Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed). |
|
|
|
```py |
|
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="prithivida/Splade_PP_en_v1") |
|
embeddings = list(model.embed(documents)) |
|
|
|
# [ |
|
# SparseEmbedding(values=array( |
|
# [0.45940185, 0.64054322, 0.2425732, 0.1623179, 1.20566428, |
|
# 0.62039357...]), |
|
# indices=array([1012, 1998, 2000, 2005, 2017, 2022...])), |
|
# SparseEmbedding(values=array([ |
|
# 0.09767706, 0.4374367, 0.00468039, 1.01167965, 1.02318227, 1.30155718 |
|
# ...]), |
|
# indices=array([2017, 2022, 2025, 2057, 2064, 2069...])) |
|
# ] |
|
|
|
``` |
