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| <title>UTC (Universal Token Classification) HandyLab App Description</title> | |
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| <h2>Welcome to UTC (Universal Token Classification) HandyLab!</h2> | |
| <h3>With UTC (Universal Token Classification) HandyLab, you can effortlessly handle following tasks:</h3> | |
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| <li><b>Named Entity Recognition (NER):</b> Identifies and categorizes entities such as names, organizations, dates, and other specific items in the text.</li> | |
| <li><b>Relation Extraction:</b> Detects and classifies relationships between entities within the text.</li> | |
| <li><b>Summarization:</b> Extract the most important sentences that summarize the input text, capturing the essential information.</li> | |
| <li><b>Sentiment Extraction:</b> Identify parts of the text that signalize a positive, negative, or neutral sentiment.</li> | |
| <li><b>Key-Phrase Extraction:</b> Identifies and extracts important phrases and keywords from the text.</li> | |
| <li><b>Question-answering:</b> Finding an answer in the text given a question.</li> | |
| <li><b>Open Information Extraction:</b> Extracts pieces of text given an open prompt from a user, for example, product description extraction.</li> | |
| <li><b>Text Cleaning:</b> Clear the text from unnecessary parts according to the prompt.</li> | |
| </ol> | |
| <h3>What is UTC (Universal Token Classification) HandyLab</h3> | |
| <p>UTC (Universal Token Classification) HandyLab serves as a foundational showcase of our technological capabilities within the universal information extraction. It enployes the model <a href="https://huggingface.co/knowledgator/UTC-DeBERTa-large-v2">"knowledgator/UTC-DeBERTa-large-v2"</a>. UTC-DeBERTa-large-v2 is a secong version of our UTC model, designed to extract various pieces of information from plain text based on a user-provided custom prompt.<p> | |
| <h3>Remember, information extraction is not just about data; it's about insights. Let's uncover those insights together!💫</h3> | |
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