Update README.md

README.md

@@ -14,11 +14,11 @@ tags:
 - zero-shot
 ---
 
-NuNER Zero is a zero-shot Named Entity Recognition (NER) Model. (In a few-shot learning setting, we recommend fine-tuning the original [NuNER](https://huggingface.co/collections/numind/nuner-token-classification-and-ner-backbones-65e1f6e14639e2a465af823b)).
+NuNER Zero is a zero-shot Named Entity Recognition (NER) Model. (In a few-shot setting, check the original [NuNER](https://huggingface.co/collections/numind/nuner-token-classification-and-ner-backbones-65e1f6e14639e2a465af823b)).
 
-NuNER Zero uses a variation of the [GLiNER](https://huggingface.co/papers/2311.08526) architecture, and takes the same input (concatenation entity types and text).
+NuNER Zero uses the [GLiNER](https://huggingface.co/papers/2311.08526) architecture: its input should be a concatenation of entity types and text.
 
-Unlike GliNER, NuNER Zero is a token classifier: it returns the infered probabilities for each token to belong to each entity type. This allow to remove the limit size of detected entities.
+Unlike GliNER, NuNER Zero is a token classifier, which allows detect arbitrary long entities.
 
 NuNER Zero was trained on NuNER v2.0 dataset, which combines subsets of Pile and C4 annotated via LLMs using [NuNER's procedure](https://huggingface.co/papers/2402.15343).