---

library_name: gguf

license: other

license_name: lfm1.0

license_link: LICENSE

language:

• en
• ar
• zh
• fr
• de
• ja
• ko
• es
• pt
• it

pipeline_tag: text-generation

base_model: LiquidAI/LFM2.5-24B-A2B

tags:

• liquid
• lfm2.5
• gguf
• llama.cpp

---

<div 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 style="display: flex; justify-content: center; gap: 0.5em; margin-bottom: 1em;">

<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://discord.com/invite/liquid-ai"><strong>Discord</strong></a>

</div>

</div>

LFM2.5-24B-A2B-GGUF

LFM2 is a new generation of hybrid models developed by Liquid AI, specifically designed for edge AI and on-device deployment. It sets a new standard in terms of quality, speed, and memory efficiency.

Find more details in the original model card: https://huggingface.co/LiquidAI/LFM2.5-24B-A2B

🏃 How to run LFM2

Example usage with llama.cpp:

llama-cli -hf LiquidAI/LFM2.5-24B-A2B-GGUF \
    --temp 0.1 --top-k 50 --repeat-penalty 1.05

The sampling parameters are the ones recommended for the base model (its generation_config.json); each GGUF also carries them as general.sampling.* metadata, so llama.cpp applies them by default.

QAD Q4_0 GGUF

The Q4_0 build in this repository is the Quantization-Aware Distillation (QAD) checkpoint,

LFM2.5-24B-A2B-QAD-Q4_0.gguf.

It was trained to recover the accuracy lost to Q4_0 quantization.

Example usage with llama.cpp:

llama-cli -hf LiquidAI/LFM2.5-24B-A2B-GGUF \
    --hf-file LFM2.5-24B-A2B-QAD-Q4_0.gguf \
    --temp 0.1 --top-k 50 --repeat-penalty 1.05