liquidai/lfm2-1.2b-extract-gguf overview

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    "base_model": "LiquidAI/LFM2-1.2B-Extract",
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    "summary": "Based on LFM2-1.2B, LFM2-1.2B-Extract is designed to **extract important information from a wide variety of unstructured documents** (such as articles, transcripts, or reports) into structured outputs like JSON, XML, or YAML. **Use cases**: You can find more information about other task-specific models in this blog post.",
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    "readme_markdown": "---\nlibrary_name: transformers\nlicense: other\nlicense_name: lfm1.0\nlicense_link: LICENSE\nlanguage:\n- en\n- ar\n- zh\n- fr\n- de\n- ja\n- ko\n- es\npipeline_tag: text-generation\ntags:\n- liquid\n- lfm2\n- edge\nbase_model: LiquidAI/LFM2-1.2B-Extract\n---\n\n<center>\n<div style=\"text-align: center;\">\n  <img \n    src=\"https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png\" \n    alt=\"Liquid AI\"\n    style=\"width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;\"\n  />\n</div>\n<div style=\"display: flex; justify-content: center; gap: 0.5em;\">\n<a href=\"https://playground.liquid.ai/\"><strong>Try LFM</strong></a> • <a href=\"https://docs.liquid.ai/lfm/getting-started/welcome\"><strong>Docs</strong></a> • <a href=\"https://leap.liquid.ai/\"><strong>LEAP</strong></a> • <a href=\"https://discord.com/invite/liquid-ai\"><strong>Discord</strong></a>\n</div>\n</center>\n\n<br>\n\n# LFM2-1.2B-Extract-GGUF\n\nBased on [LFM2-1.2B](https://huggingface.co/LiquidAI/LFM2-1.2B), LFM2-1.2B-Extract is designed to **extract important information from a wide variety of unstructured documents** (such as articles, transcripts, or reports) into structured outputs like JSON, XML, or YAML.\n\n**Use cases**:\n\n- Extracting invoice details from emails into structured JSON.\n- Converting regulatory filings into XML for compliance systems.\n- Transforming customer support tickets into YAML for analytics pipelines.\n- Populating knowledge graphs with entities and attributes from unstructured reports.\n\nYou can find more information about other task-specific models in this [blog post](https://www.liquid.ai/blog/introducing-liquid-nanos-frontier-grade-performance-on-everyday-devices).\n\n## 🏃 How to run LFM2\n\nExample usage with [llama.cpp](https://github.com/ggml-org/llama.cpp):\n\n```\nllama-cli -hf LiquidAI/LFM2-1.2B-Extract-GGUF\n```",
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  "last_modified": "2026-04-06T18:53:24.000Z",
  "created_at": "2025-09-05T15:57:40.000Z",
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