Update app.py

app.py

@@ -10,7 +10,7 @@ st.title("SelfCheck scores")
 
 @st.cache_data
 def load_data(min_score=0.4, exclude_stories=True):
-    ds = load_dataset("HuggingFaceTB/hallucinations_450_samples_scores", split="train", token=HF_TOKEN, num_proc=2)
+    ds = load_dataset("loubnabnl/comsop_450_samples_detailed", split="train", token=HF_TOKEN, num_proc=2)
     ds = ds.filter(lambda x: x["passage_score"] >= min_score)
     if exclude_stories:
         ds = ds.filter(lambda x: "story" not in x["format"])
@@ -27,4 +27,11 @@ index = st.number_input(f'Found {len(ds)} samples, choose one', min_value=0, max
 sample = ds[index]
 st.markdown(f"**Passage Score:** {sample['passage_score']:.2f}, **seed data**: {sample['seed_data']}, **format**: {sample['format']}.")
 st.markdown("---")
-st.markdown(sample['original_text'])
+st.markdown(sample['original_text'])
+
+# get inconsistent sentences
+st.subheader("🤔 Sentences with a high inconsistency score")
+sentences = sample["sentences_and_scores"]
+sentences = [e for e in sentences if e["score"] > 0.5]
+for s in sentences:
+    st.markdown(s['sentence'])