Fix invalid link reference of reference-free model in readme

README.md

@@ -123,7 +123,7 @@ Your source and samples file should be [formatted in this way](https://unbabel.g
 Within COMET, there are several evaluation models available. You can refer to the [MODELS](MODELS.md) page for a comprehensive list of all available models. Here is a concise list of the main reference-based and reference-free models:
 
 - **Default Model:** [`Unbabel/wmt22-comet-da`](https://huggingface.co/Unbabel/wmt22-comet-da) - This model employs a reference-based regression approach and is built upon the XLM-R architecture. It has been trained on direct assessments from WMT17 to WMT20 and provides scores ranging from 0 to 1, where 1 signifies a perfect translation.
-- **Reference-free Model:** [`Unbabel/wmt22-cometkiwi-da`](https://huggingface.co/Unbabel/wmt23-cometkiwi-da) - This reference-free model employs a regression approach and is built on top of InfoXLM. It has been trained using direct assessments from WMT17 to WMT20, as well as direct assessments from the MLQE-PE corpus. Similar to other models, it generates scores ranging from 0 to 1. For those interested, we also offer larger versions of this model: [`Unbabel/wmt23-cometkiwi-da-xl`](https://huggingface.co/Unbabel/wmt23-cometkiwi-da-xl) with 3.5 billion parameters and [`Unbabel/wmt23-cometkiwi-da-xxl`](https://huggingface.co/Unbabel/wmt23-cometkiwi-da-xxl) with 10.7 billion parameters.
+- **Reference-free Model:** [`Unbabel/wmt22-cometkiwi-da`](https://huggingface.co/Unbabel/wmt22-cometkiwi-da) - This reference-free model employs a regression approach and is built on top of InfoXLM. It has been trained using direct assessments from WMT17 to WMT20, as well as direct assessments from the MLQE-PE corpus. Similar to other models, it generates scores ranging from 0 to 1. For those interested, we also offer larger versions of this model: [`Unbabel/wmt23-cometkiwi-da-xl`](https://huggingface.co/Unbabel/wmt23-cometkiwi-da-xl) with 3.5 billion parameters and [`Unbabel/wmt23-cometkiwi-da-xxl`](https://huggingface.co/Unbabel/wmt23-cometkiwi-da-xxl) with 10.7 billion parameters.
 - **eXplainable COMET (XCOMET):** [`Unbabel/XCOMET-XXL`](https://huggingface.co/Unbabel/XCOMET-XXL) - Our latest model is trained to identify error spans and assign a final quality score, resulting in an explainable neural metric. We offer this version in XXL with 10.7 billion parameters, as well as the XL variant with 3.5 billion parameters ([`Unbabel/XCOMET-XL`](https://huggingface.co/Unbabel/XCOMET-XL)). These models have demonstrated the highest correlation with MQM and are our best performing evaluation models.
 
 Please be aware that different models may be subject to varying licenses. To learn more, kindly refer to the [LICENSES.models](LICENSE.models.md) and model licenses sections.