commited

README.md

@@ -1,12 +1,16 @@
----
-title: EmotionsApp
-emoji: 🏢
-colorFrom: yellow
-colorTo: pink
-sdk: gradio
-sdk_version: 5.30.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Gradio Emotion Detection App
+
+This app uses a fine-tuned BERT model (GoEmotions) to detect emotions in social media text.
+
+## Run Locally
+
+```bash
+pip install -r requirements.txt
+python app.py
+```
+
+## For Hugging Face Spaces
+
+1. Upload this project to your new Space.
+2. Make sure you upload the `bert-base-goemotions-ekman` model folder inside `models/`.
+3. Hugging Face will automatically run `app.py`.

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the model locally (assuming model files are in this folder)
+classifier = pipeline("text-classification", model="./models/bert-base-goemotions-ekman", return_all_scores=True)
+
+def detect_emotions(text):
+    results = classifier(text)[0]
+    sorted_results = sorted(results, key=lambda x: x["score"], reverse=True)
+    return {r['label']: round(r['score'], 3) for r in sorted_results}
+
+demo = gr.Interface(
+    fn=detect_emotions,
+    inputs=gr.Textbox(lines=4, placeholder="Enter a tweet or comment..."),
+    outputs="label",
+    title="Emotion Detection with BERT (GoEmotions)",
+    description="Detect joy, sadness, anger, and other emotions from text using a BERT-based model fine-tuned on the GoEmotions dataset."
+)
+
+demo.launch()

models/bert-base-goemotions-ekman/README.txt

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+Place your downloaded Hugging Face model files here from:
+https://huggingface.co/bhadresh-savani/bert-base-goemotions-ekman

requirements.txt

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+gradio
+transformers
+torch