Sentiment Analyzer
Detect positive or negative sentiment in any text using AI — runs entirely in your browser, nothing uploaded.
All processing runs entirely in your browser using WebAssembly. No image or text is ever uploaded to a server. First run downloads the AI model (~44–70 MB) and caches it locally — subsequent runs are instant.
Sentiment Analyzer — AI-Powered Text Sentiment Detection
This tool uses DistilBERT fine-tuned on the Stanford Sentiment Treebank 2 (SST-2) dataset to classify text as positive or negative. DistilBERT is a lightweight transformer model that retains 97% of BERT's accuracy at 40% of the size, making it practical for in-browser inference via WebAssembly. The model (~70 MB) downloads once and is cached locally. Use it to analyse customer reviews, social media posts, survey responses, or any free-text feedback. Results include a confidence percentage for each class. Nothing is uploaded; all inference runs on your device.
Private & free — this tool runs entirely in your browser.
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