Emotion detection space.

.streamlit/config.toml

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+[theme]
+base="light"
+primaryColor="#d756ff"

README.md

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 ---
 title: Emotion Detection
-emoji: 👁
-colorFrom: gray
-colorTo: gray
+emoji: 💜
+colorFrom: blue
+colorTo: purple
 sdk: streamlit
 sdk_version: 1.17.0
 app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import streamlit as st
+from transformers import pipeline
+
+@st.cache_resource(show_spinner="Loading model...")
+def load_pipe():
+    pipe = pipeline(task="text-classification", model="cnicu/tweet_emotions_classifier")
+    return pipe
+
+def classify_emotion(text: str, pipe: pipeline) -> str:
+    prediction = pipe(text)
+    return prediction
+
+st.title("Tweet emotions classification")
+
+text = st.text_area("Tweet to classify", label_visibility='hidden')
+
+if st.button("Classify tweet", disabled= text == ''):
+    with st.spinner("In progress..."):
+        prediction = classify_emotion(text, load_pipe())
+        st.success(f"Tweet's emotion: **{prediction[0]['label']}**")

requirements.txt

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+streamlit
+transformers