Upload app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+from transformers import AutoTokenizer as AT, AutoModelForSequenceClassification as AFSC
+
+modName = "madhurjindal/autonlp-Gibberish-Detector-492513457" # Gibberish Detection Model from HuggingFace
+
+mod = AFSC.from_pretrained(modName)
+TKR = AT.from_pretrained(modName)
+
+st.title("Gibberish Detector")
+
+user_input = str(st.text_input("Enter some words", "pasghetti"))
+
+st.markdown("Input was: ", str(user_input))
+
+classifier = pipeline("sentiment-analysis", model=mod, tokenizer=TKR)
+# result = classifier(["This is a sample text made by Sean Ramirez.", "This is another sample text."]) # leftover from initial testing
+
+if user_input is not None:
+    col = st.columns(1)
+    predicts = pipeline("sentiment-analysis", model=mod, tokenizer=TKR)
+
+    col.header("Probabilities")
+    for p in predicts:
+        col.subheader(f"{ p['label']}: { round(p['score'] * 100, 1)}%")