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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) | |
result = pipeline("sentiment-analysis", model=mod, tokenizer=TKR) | |
st.title("Gibberish Detector") | |
user_input = str(st.text_input("Enter some words", "pasghetti")) | |
# result = classifier(["This is a sample text made by Sean Ramirez.", "This is another sample text."]) # leftover from initial testing | |
if user_input: | |
predicts = result(user_input)[0] | |
st.markdown("## Probabilities") | |
st.write(f"Predicted: { predicts['label'] }") | |
st.write(f"Score: { round(predicts['score'] * 100, 1)}%") | |