初始化项目，由ModelHub XC社区提供模型

Model: LiquidAI/LFM2-350M-Extract-GGUF
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: other
+license_name: lfm1.0
+license_link: LICENSE
+language:
+- en
+- ar
+- zh
+- fr
+- de
+- ja
+- ko
+- es
+pipeline_tag: text-generation
+tags:
+- liquid
+- lfm2
+- edge
+base_model: LiquidAI/LFM2-350M-Extract
+---
+
+<center>
+<div style="text-align: center;">
+  <img 
+    src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png" 
+    alt="Liquid AI"
+    style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
+  />
+</div>
+<div style="display: flex; justify-content: center; gap: 0.5em;">
+<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>
+</div>
+</center>
+
+<br>
+
+# LFM2-350M-Extract-GGUF
+
+Based on [LFM2-350M](https://huggingface.co/LiquidAI/LFM2-350M), LFM2-350M-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**:
+
+- Extracting invoice details from emails into structured JSON.
+- Converting regulatory filings into XML for compliance systems.
+- Transforming customer support tickets into YAML for analytics pipelines.
+- Populating knowledge graphs with entities and attributes from unstructured reports.
+
+You 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).
+
+## 🏃 How to run LFM2
+
+Example usage with [llama.cpp](https://github.com/ggml-org/llama.cpp):
+
+```
+llama-cli -hf LiquidAI/LFM2-350M-Extract-GGUF
+```