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  ---
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- title: Space 10
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- emoji: 👁
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- colorFrom: purple
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- colorTo: green
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  sdk: gradio
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- sdk_version: 6.10.0
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  app_file: app.py
 
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  pinned: false
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  ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ title: Multilingual Emotion Recognition (EN / SI / TA)
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+ emoji: 😊
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+ colorFrom: indigo
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+ colorTo: purple
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  sdk: gradio
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+ sdk_version: 4.44.0
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  app_file: app.py
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+ python_version: 3.11
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  pinned: false
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  ---
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+ # Multilingual Text Emotion Recognition App
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+ **English • සිංහල • தமிழ்**
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+
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+ This is a simple web app that detects emotions from text in three languages:
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+
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+ - **English** → Logistic Regression + TF-IDF (classical ML model)
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+ - **Sinhala** → Finetuned transformer model
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+ - **Tamil** → Finetuned transformer model
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+
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+ ### Supported Languages & Models
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+ | Language | Model Type | Repository on Hugging Face |
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+ |------------|-------------------------|------------------------------------------------------------------|
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+ | English | TF-IDF + Logistic Regression | E-motionAssistant/Englsih_Trained_Model_LR |
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+ | Sinhala | Finetuned Transformer | E-motionAssistant/SInhala_Text_Emotion_Recognition_Model |
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+ | Tamil | Finetuned Transformer | E-motionAssistant/Tamil_Emotion_Recognition_Model |
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+
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+ ### How to Use
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+ 1. Go to one of the tabs (English / සිංහල / தமிழ்)
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+ 2. Type or paste your text/message/tweet
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+ 3. The app will show the predicted emotion + confidence score
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+
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+ ### Examples
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+ - English: "I hate mondays so much" → likely **sadness** or **anger**
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+ - Sinhala: "මම ගොඩක් දුකින් ඉන්නවා" → likely **sadness**
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+ - Tamil: "எனக்கு ரொம்ப கோபமா இருக்கு" → likely **anger**
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+
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+ ### Technical Notes
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+ - Built with **Gradio** (v4.44.0)
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+ - Models are downloaded from Hugging Face at startup (using `hf_hub_download` and `pipeline`)
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+ - Uses **Python 3.11** to avoid compatibility issues
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+ - No GPU required — runs on CPU
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+
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+ ### Want to run locally?
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+ ```bash
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+ git clone https://huggingface.co/spaces/YOUR_USERNAME/Space4
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+ cd Space4
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+ pip install -r requirements.txt
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+ python app.py