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- <title>UTC (Universal Token Classification) HandyLab App Description</title>
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- border: 1px solid grey; /* Added border to make the button visible against white background */
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- color: #007bff; /* Text color changed to make it visible against white background */
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- }
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- </style>
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- </head>
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- <body>
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- <h2>Welcome to GliClass SandBox!</h2>
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- <h3>GLiClass: Generalist and Lightweight Model for Sequence Classification:</h3>
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- <ol>
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- <li><b>Zero-Shot text classification</b></li>
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- <li><b>Topic Classification</b></li>
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- <li><b>Sentiment Analysis</b></li>
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- <li><b>Reranker in RAG pipelines</b></li>
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- </ol>
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- <h3>What is GliClass?</h3>
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- <p>This is an efficient zero-shot classifier inspired by <a href="https://github.com/urchade/GLiNER/tree/main">"GLiNER"</a> work. It demonstrates the same performance as a cross-encoder while being more compute-efficient because classification is done at a single forward path. It can be used for topic classification, sentiment analysis and as a reranker in RAG pipelines.<p>
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- <h3>Remember, information extraction is not just about data; it's about insights. Let's uncover those insights together!💫</h3>
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