---
license: mit
inference: false
language:
- en
---

# sle-base

This is a model for the SLE metric described in the original paper. It is based on [`roberta-base`](https://huggingface.co/roberta-base) with an added regression head.

Install the [python library](https://github.com/liamcripwell/sle).

SLE scores can be calculated within python as shown in the example below.

For a raw estimation of a sentence's simplicity, use `'sle'`, but to evaluate sentence simplification systems we recommend providing the input sentences and using `'sle_delta'` ($\Delta \text{SLE}$). See the paper for further details.


```python
from sle.scorer import SLEScorer

scorer = SLEScorer("liamcripwell/sle-base")

texts = [
  "Here is a simple sentence.",
  "Here is an additional sentence that makes use of more complex terminology."
]

# raw simplicity estimates
results = scorer.score(texts)
print(results) # {'sle': [3.9842946529388428, 0.5840105414390564]}

# delta from input sentences
results = scorer.score([texts[0]], inputs=[texts[1]])
print(results) # {'sle': [3.9842941761016846], 'sle_delta': [3.4002838730812073]}
```