File size: 1,977 Bytes
d3ec202 99622a8 474cfeb d3ec202 b1ad001 b309b5b d3ec202 b309b5b 349781b d0313d4 896a8e7 349781b 8fed163 349781b a71b5ff 349781b a71b5ff 349781b b309b5b 474cfeb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 |
---
language:
- en
license: apache-2.0
tags:
- sentence-similarity
- feature-extraction
- transformers
- sentence-transformers
- luxical
---
# 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)
```
|