Extract named entities from text
Visual RAG Tool
Upload and analyze documents for text extraction and Q&A
Traditional OCR 1.0 on PDF/image files returning text/PDF
Process text to extract entities and details
Find information using text queries
Answer questions based on provided text
Search and summarize documents with natural language queries
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Dslim Bert Base NER is an AI model designed for Named Entity Recognition (NER) tasks. It leverages the BERT base architecture, fine-tuned for high accuracy in extracting named entities from text. This model is particularly effective for processing scanned documents, making it a robust tool for information extraction in various applications.
1. Can I use Dslim Bert Base NER for custom entity recognition tasks?
Yes, the model can be fine-tuned for custom entity recognition tasks by providing additional training data.
2. Does Dslim Bert Base NER support non-English text?
Currently, Dslim Bert Base NER is optimized for English text. For non-English text, you may need to use a different model or fine-tune this model for your specific language.
3. Can I process large documents with Dslim Bert Base NER?
Absolutely! The model supports batch processing, making it efficient for handling large volumes of text extracted from scanned documents.