初始化项目，由ModelHub XC社区提供模型

Model: LiquidAI/LFM2-24B-A2B-GGUF
Source: Original Platform

README.md

@@ -0,0 +1,67 @@
+---
+library_name: transformers
+license: other
+license_name: lfm1.0
+license_link: LICENSE
+language:
+- en
+- ar
+- zh
+- fr
+- de
+- ja
+- ko
+- es
+- pt
+pipeline_tag: text-generation
+tags:
+- liquid
+- lfm2
+- edge
+- moe
+- llama.cpp
+- gguf
+base_model:
+- LiquidAI/LFM2-24B-A2B
+---
+
+<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>
+
+# LFM2-24B-A2B-GGUF
+
+LFM2 is a family of hybrid models designed for on-device deployment. LFM2-24B-A2B is the largest model in the family, scaling the architecture to 24 billion parameters while keeping inference efficient.
+
+- **Best-in-class efficiency**: A 24B MoE model with only 2B active parameters per token, fitting in 32 GB of RAM for deployment on consumer laptops and desktops.
+- **Fast edge inference**: 112 tok/s decode on AMD CPU, 293 tok/s on H100. Fits in 32B GB of RAM with day-one support llama.cpp, vLLM, and SGLang.
+- **Predictable scaling**: Quality improves log-linearly from 350M to 24B total parameters, confirming the LFM2 hybrid architecture scales reliably across nearly two orders of magnitude.
+
+![image](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/VhdjtAT5zWTWdVYgW69O0.png)
+
+Find more information about LFM2-24B-A2B in our [blog post](https://www.liquid.ai/blog/).
+
+## How to run LFM2
+
+Example usage with [llama.cpp](https://github.com/ggml-org/llama.cpp):
+
+```
+llama-cli -hf LiquidAI/LFM2-24B-A2B-GGUF --conversation \
+    --temp 0.1 --top-k 50 --repeat-penalty 1.05
+```
+
+## 📬 Contact
+
+- Got questions or want to connect? [Join our Discord community](https://discord.com/invite/liquid-ai)
+- If you are interested in custom solutions with edge deployment, please contact [our sales team](https://www.liquid.ai/contact).