Update README.md

README.md

@@ -79,7 +79,7 @@ Neural networks come from different sources. With `thingsvision`, you can extrac
 - both original [CLIP](https://github.com/openai/CLIP) variants (`ViT-B/32` and `RN50`)
 - a few custom models (Alexnet, VGG-16, Resnet50, and Inception_v3) trained on [Ecoset](https://www.pnas.org/doi/10.1073/pnas.2011417118) rather than ImageNet  and one Alexnet pretrained on ImageNet and fine-tuned on [SalObjSub](https://cs-people.bu.edu/jmzhang/sos.html)
 - each of the many [CORnet](https://github.com/dicarlolab/CORnet) versions
-- [Harmonization](https://arxiv.org/abs/2211.04533) models from the official [Harmonization repo](https://github.com/serre-lab/harmonization). The default variant is `ViT_B16`. However, the following encoders are additionally available: `ResNet50`, `VGG16`, `EfficientNetB0`, `tiny_ConvNeXT`, `tiny_MaxViT`, `LeViT_small`<br> 
+- [Harmonization](https://arxiv.org/abs/2211.04533) models from the official [Harmonization repo](https://github.com/serre-lab/harmonization). The default variant is `ViT_B16`. Other available models are `ResNet50`, `VGG16`, `EfficientNetB0`, `tiny_ConvNeXT`, `tiny_MaxViT`, `LeViT_small`<br> 
 - [DreamSim](https://dreamsim-nights.github.io/) models from the official [DreamSim repo](https://github.com/ssundaram21/dreamsim). The default variant is `open_clip_vitb32`. Other available models are `clip_vitb32`. See the [docs](https://vicco-group.github.io/thingsvision/AvailableModels.html) for more information.
 
 <p align="right">(<a href="#readme-top">back to top</a>)</p>