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| title: SenseCatch | |
| emoji: 🎭 | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: docker | |
| app_port: 7860 | |
| pinned: false | |
| license: mit | |
| short_description: Sentiment analysis with seven selectable models | |
| # SenseCatch | |
| SenseCatch labels English review text as Positive or Negative. It serves seven selectable models from a single container: four classical machine learning models (Naive Bayes, Logistic Regression, LinearSVC, NBSVM), a DistilBERT transformer fine-tuned on IMDB, a stacked ensemble that combines them, and an optional rule-based mode. | |
| The first request after the Space has been idle is slow, because the container wakes from sleep and loads the models on demand. Later requests are fast. | |
| Source code: https://github.com/berkinksk/SenseCatch | |