README.md

---
language:
- en
license: apache-2.0
tags:
- sentence-similarity
- feature-extraction
- transformers
- sentence-transformers
- luxical
---

![Luxical_logo](https://cdn-uploads.huggingface.co/production/uploads/665befa320dee2925d7c1d51/A5VPoshn_6p_zdHHeZdJi.png)

# Luxical-One

Luxical-One is a small lexical-dense text embedding model distilled from [`Snowflake/snowflake-arctic-embed-m-v2.0`](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v2.0). It is optimized for high-throughput embedding without GPU acceleration, and it is trained for English-language symmetrical full-document text similarity and classification applications.

Read the full story of Luxical in our [blog post](https://www.datologyai.com/blog/introducing-luxical-embeddings).

Want to go deeper with Luxical models? Check out the [repo](https://github.com/datologyai/luxical).

## Quickstart

Luxical-One includes a basic HuggingFace integration that supports model inference. GPU-based inference is not supported (GPU "acceleration" would not provide a meaningful boost on most systems due to how fast and small the model is anyhow).

You must have the `luxical` package installed to run this model, and you must trust the remote code bundled with the model. Currently only cpython versions 3.11-3.13 and macos/linux operating systems are supported. 


To install `luxical`:
``` shell
pip install luxical
```

To load and use the model in `transformers`:
``` python
from transformers import AutoModel

example_text = "Luxical integrates with Huggingface."
luxical_one = AutoModel.from_pretrained("datologyai/luxical-one", trust_remote_code=True)
embeddings = luxical_one([example_text]).embeddings
```

Or via `sentence-transformers`:
```python
from sentence_transformers import SentenceTransformer

example_text = "Luxical integrates with Huggingface."
luxical_one = SentenceTransformer("datologyai/luxical-one", trust_remote_code=True)
embeddings = luxical_one.encode(example_text)
```