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| title: SEMA | |
| emoji: 📈 | |
| colorFrom: indigo | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 5.25.2 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: 'SEMA: Analyze sentence similarity, sentiment, and more' | |
| # 🧪 SEMA: Semantic Evaluation & Matching Analyzer | |
| SEMA is an interactive Gradio-powered NLP tool for analyzing semantic similarity, paraphrasing, sentiment, and linguistic features between two sentences. | |
| ## 🚀 Features | |
| - ✅ Sentence similarity scoring (BERT/SBERT models) | |
| - 📊 Visual similarity charts (Bar, Gauge, Heatmap) | |
| - 🔄 Paraphrase detection and generation | |
| - 💬 Sentiment analysis (transformers-based) | |
| - 🧠 Named Entity Recognition (NER) | |
| - 🧾 POS tagging with visual distribution (Pie chart) | |
| - 📚 Text statistics: word counts, overlap, character counts | |
| ## 🔧 Models Used | |
| - Sentence Transformers: | |
| - `all-MiniLM-L6-v2` | |
| - `paraphrase-MiniLM-L3-v2` | |
| - `paraphrase-multilingual-MiniLM-L12-v2` | |
| - `distilbert-base-nli-mean-tokens` | |
| - Paraphraser: `ramsrigouthamg/t5_paraphraser` | |
| - Sentiment: Hugging Face sentiment-analysis pipeline | |
| - NER/POS: spaCy (`en_core_web_trf`) | |
| ## 🛠️ Setup | |
| ```bash | |
| git clone https://github.com/adityasync/SEMA.git | |
| cd SEMA | |
| pip install -r requirements.txt | |
| python app.py | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |