Librarian Bot: Update dataset YAML metadata for model

This is a pull request to add a dataset, [`KBLab/sucx3_ner`](https://huggingface.co/datasets/KBLab/sucx3_ner), to the metadata for your model (defined in the `YAML` block of your model's `README.md`).
The pull request was made by [librarian-bot](https://huggingface.co/librarian-bot) and used a combination of rules and/or machine learning to suggest this additional metadata.
If this suggestion is incorrect, feel free to close this pull request.

Librarian Bot was made by [@davanstrien](https://huggingface.co/davanstrien); feel free to get in touch with feedback.

README.md

@@ -1,75 +1,11 @@
 ---
-tags:
-- spacy
-- token-classification
 language:
 - sv
 license: cc-by-sa-4.0
-model-index:
-- name: sv_core_news_lg
-  results:
-  - task:
-      name: NER
-      type: token-classification
-    metrics:
-    - name: NER Precision
-      type: precision
-      value: 0.8602032409
-    - name: NER Recall
-      type: recall
-      value: 0.7620437956
-    - name: NER F Score
-      type: f_score
-      value: 0.8081537866
-  - task:
-      name: TAG
-      type: token-classification
-    metrics:
-    - name: TAG (XPOS) Accuracy
-      type: accuracy
-      value: 0.9509033378
-  - task:
-      name: POS
-      type: token-classification
-    metrics:
-    - name: POS (UPOS) Accuracy
-      type: accuracy
-      value: 0.9637644177
-  - task:
-      name: MORPH
-      type: token-classification
-    metrics:
-    - name: Morph (UFeats) Accuracy
-      type: accuracy
-      value: 0.9584566704
-  - task:
-      name: LEMMA
-      type: token-classification
-    metrics:
-    - name: Lemma Accuracy
-      type: accuracy
-      value: 0.9555986526
-  - task:
-      name: UNLABELED_DEPENDENCIES
-      type: token-classification
-    metrics:
-    - name: Unlabeled Attachment Score (UAS)
-      type: f_score
-      value: 0.8362874455
-  - task:
-      name: LABELED_DEPENDENCIES
-      type: token-classification
-    metrics:
-    - name: Labeled Attachment Score (LAS)
-      type: f_score
-      value: 0.7879268362
-  - task:
-      name: SENTS
-      type: token-classification
-    metrics:
-    - name: Sentences F-Score
-      type: f_score
-      value: 0.9364613881
+tags:
+- spacy
+- token-classification
+datasets: KBLab/sucx3_ner
 ---
 ### Details: https://spacy.io/models/sv#sv_core_news_lg