README.md

metadata

license: other
license_name: lfm1.0
license_link: LICENSE
language:
  - en
tags:
  - liquid
  - lfm2.5
  - edge
  - llama.cpp
  - audio
  - speech
  - gguf
base_model:
  - LiquidAI/LFM2.5-Audio-1.5B
widget:
  - text: Demo
    output:
      url: demo.mp4

Try LFM • Docs • LEAP • Discord

LFM2.5-Audio-1.5B

Find more details in the original model card: https://huggingface.co/LiquidAI/LFM2.5-Audio-1.5B

Runners

runners folder contains runners for various architectures including

• llama-liquid-audio-cli
• llama-liquid-audio-server

🏃 How to run LFM2.5

CLI

Set env variables.

export CKPT=/path/to/LFM2.5-Audio-1.5B-GGUF
export INPUT_WAV=/path/to/input.wav
export OUTPUT_WAV=/path/to/output.wav

ASR (audio -> text)

./llama-liquid-audio-cli -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf -sys "Perform ASR." --audio $INPUT_WAV

TTS (text -> audio)

./llama-liquid-audio-cli -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf -sys "Perform TTS." -p "Hi, how are you?" --output $OUTPUT_WAV

Interleaved (audio/text -> audio + text)

./llama-liquid-audio-cli -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf -sys "Respond with interleaved text and audio." --audio $INPUT_WAV --output $OUTPUT_WAV

Server

Start server

export CKPT=/path/to/LFM2.5-Audio-1.5B-GGUF
./llama-liquid-audio-server -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf

Use liquid_audio_chat.py script to communicate with the server.

uv run liquid_audio_chat.py

Source Code for Runners

Runners are built from https://github.com/ggml-org/llama.cpp/pull/18641. It's WIP and will take time to land in upstream.

Demo

Prompt

Demo