Update README.md

README.md

@@ -41,7 +41,7 @@ model-index:
 >
 > For real workloads, please use the base [Toto 2.0 collection](https://huggingface.co/collections/Datadog/toto-20). The base checkpoints are pretrained without any public data, generalize to every benchmark we have evaluated, and are what we recommend deploying.
 
-## ✨ What this is
+## ✨ What this is?
 
 A per-`(frequency, term)` XGBoost gate over a pool of 10 foundation models (5 Toto 2.0 sizes + 5 external models). The meta-learner consumes lightweight tsfeatures from each forecast window and emits a softmax over the model pool; the final forecast is the weighted sum of the 10 base-model quantile predictions. Following the [FFORMA](https://www.sciencedirect.com/science/article/abs/pii/S0169207019300895) framework (Montero-Manso et al., 2020).
 
@@ -124,7 +124,3 @@ Each base model's predictions were generated by running its standard GIFT-Eval n
 ```bibtex
 (citation coming soon)
 ```
-
-## 📝 License
-
-Apache 2.0. Each base model retains its original license — see the linked HF repos in the model pool table.