LiquidAI/LFM3-1.7B-GGUF
Summary
Liquid AI 发布 LFM3-1.7B 的 GGUF 版本,支持在 CPU/GPU 上本地推理,兼容 llama.cpp、Ollama、LM Studio 等工具,并提供经过量化感知蒸馏(QAD)的 Q4_0 检查点以恢复量化损失的精度。
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LiquidAI/LFM3-1.7B-GGUF · Hugging Face
Source: https://huggingface.co/LiquidAI/LFM3-1.7B-GGUF

GGUF version ofLFM3-1.7Bfor local inference on CPUs and GPUs.
Find architecture and usage details in theoriginal model card.
https://huggingface.co/LiquidAI/LFM3-1.7B-GGUF#how-to-run-lfm3-17bHow to run LFM3-1.7B
Recommended sampling: temperature 0.1, top_k 50, repeat penalty 1.1. For math and science: temperature 1.0, top_p 0.95, top_k 20.
- Llama.app(Use this model > Llamain the menu), for macOS and Windows. Requires llama.cpp versionv0.8.0or newer.
- LM Studio(Use this model > LM Studioin the menu), for macOS, Windows and Linux. Requires LM Studio with llama.cpp engine 2.65.1 or newer.
- Ollama(
ollama run lfm3), for macOS. Requires Ollama versionv0.40.12or newer.
https://huggingface.co/LiquidAI/LFM3-1.7B-GGUF#use-with-llamacppUse with llama.cpp
Add a quantization tag to pick a file.
llama-cli -hf LiquidAI/LFM3-1.7B-GGUF:Q4_K_M \
--temp 0.1 --top-k 50 --repeat-penalty 1.1
For math and science, use\-\-temp 1\.0 \-\-top\-p 0\.95 \-\-top\-k 20instead. More options in thellama.cpp guide.
https://huggingface.co/LiquidAI/LFM3-1.7B-GGUF#qad-q4_0-ggufQAD Q4_0 GGUF
The Q4_0 build in this repository is the Quantization-Aware Distillation (QAD) checkpoint,LFM3\-1\.7B\-QAD\-Q4\_0\.gguf. It was trained to recover the accuracy lost to Q4_0 quantization.
Example usage withllama.cpp:
llama-cli -hf LiquidAI/LFM3-1.7B-GGUF \
--hf-file LFM3-1.7B-QAD-Q4_0.gguf \
--temp 0.1 --top-k 50 --repeat-penalty 1.1
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