Fix: Added .strip() to all ScandiProb input text + slight markdown changes again

app.py

@@ -63,7 +63,8 @@ def da_no_cross_skew(text):
     return [no_skew, da_skew]
 
 def ScandiProb(text):
-    if not text.strip():
+    text = text.strip()
+    if not text:
         return "None", {label: 0.0 for label in labels}
         
     inputs = tokenizer(text, return_tensors="pt")
@@ -106,8 +107,8 @@ with gr.Blocks() as demo:
     gr.Markdown("# ScandiProb: Hybrid Language ID Classifier")
     gr.Markdown("### By Ian Rodriguez")
     gr.Markdown("Enter text to output independent probabilities that it is written in **Norwegian**, **Swedish**, **Danish**, or **None of the Above / Non-Scandinavian**.")
-    gr.Markdown("This model utilizes a fine-tuned [ScandiBERT](https://huggingface.co/vesteinn/ScandiBERT), trained on limited amounts of [OPUS-100](https://huggingface.co/datasets/Helsinki-NLP/opus-100/), combined with regex-enforced heuristics. Achieves ~84% macro-F1 score on the [SLIDE eval set](https://huggingface.co/datasets/ltg/slide) with a fraction of the training data used in the 2025 SLIDE paper.")
-    gr.Markdown("[This project is licensed under AGPL-3.0.](https://www.gnu.org/licenses/agpl-3.0.en.html).")
+    gr.Markdown("This model utilizes a fine-tuned [ScandiBERT](https://huggingface.co/vesteinn/ScandiBERT), trained on limited amounts of [OPUS-100](https://huggingface.co/datasets/Helsinki-NLP/opus-100/), combined with regex-enforced heuristics. Achieves ~84% macro-F1 score on the comprehensive [SLIDE eval set](https://huggingface.co/datasets/ltg/slide) with a fraction of the training data used in the 2025 SLIDE paper.")
+    gr.Markdown("[This project is licensed under AGPL-3.0.](https://www.gnu.org/licenses/agpl-3.0.en.html)")
     gr.Markdown("([GitHub](https://github.com/cloudeerie/scandiprob) | [Kaggle Notebooks](https://www.kaggle.com/code/cloudeerie/scandiprob/))")
     
     with gr.Row():